@article {28078,
	title = {Adaptive Edge Association for Wireless Digital Twin Networks in 6G},
	journal = { IEEE Internet of Things Journal},
	volume = {8},
	year = {2021},
	month = {07/2021},
	pages = {16219-16230},
	publisher = { IEEE},
	abstract = {6G is envisioned to be characterized by ubiquitous connectivity, extremely low latency, and enhanced edge intelligence. However, enriching 6G with these features requires addressing new, unique and complex challenges specifically at the edge of the network. In this paper, we propose a wireless digital twin edge network model by integrating digital twin with edge networks to enable new functionalities such as hyper-connected experience and low-latency edge computing. To efficiently construct and maintain digital twins in the wireless digital twin network, we formulate the edge association problem with respect to the dynamic network states and varying network topology. Furthermore, according to the different running stages, we decompose the problem into two sub-problems, including digital twin placement and digital twin migration. Moreover, we develop a Deep Reinforcement Learning (DRL) based algorithm to find the optimal solution to the digital twin placement problem, and then use transfer learning to solve the digital twin migration problem. Numerical results show that the proposed scheme provides reduced system cost and enhanced convergence rate for dynamic network states.},
	doi = {10.1109/JIOT.2021.3098508},
	author = {Lu, Yunlong and Maharjan, Sabita and Zhang, Yan}
}
@article {28070,
	title = {Communication-efficient Federated Learning and Permissioned Blockchain for Digital Twin Edge Networks},
	journal = { IEEE Internet of Things Journal},
	volume = {8},
	year = {2021},
	month = {02/2021},
	publisher = { IEEE},
	abstract = {Emerging technologies, such as mobile-edge computing (MEC) and next-generation communications are crucial for enabling rapid development and deployment of the Internet of Things (IoT). With the increasing scale of IoT networks, how to optimize the network and allocate the limited resources to provide high-quality services remains a major concern. The existing work in this direction mainly relies on models that are of less practical value for resource-limited IoT networks, and can hardly simulate the dynamic systems in real time. In this article, we integrate digital twins with edge networks and propose the digital twin edge networks (DITENs) to fill the gap between physical edge networks and digital systems. Then, we propose a blockchain-empowered federated learning scheme to strengthen communication security and data privacy protection in DITEN. Furthermore, to improve the efficiency of the integrated scheme, we propose an asynchronous aggregation scheme and use digital twin empowered reinforcement learning to schedule relaying users and allocate spectrum resources. Theoretical analysis and numerical results confirm that the proposed scheme can considerably enhance both communication efficiency and data security for IoT applications.},
	author = {Lu, Yunlong and Huang, Xiaohong and Zhang, Ke and Maharjan, Sabita and Zhang, Yan}
}
@article {28074,
	title = {Communication-Efficient Federated Learning for Digital Twin Edge Networks in Industrial IoT},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {17},
	year = {2021},
	month = {08/2021},
	publisher = { IEEE},
	abstract = {The rapid development of artificial intelligence and 5G paradigm, opens up new possibilities for emerging applications in industrial Internet of Things (IIoT). However, the large amount of data, the limited resources of Internet of Things devices, and the increasing concerns of data privacy, are major obstacles to improve the quality of services in IIoT. In this article, we propose the digital twin edge networks (DITENs) by incorporating digital twin into edge networks to fill the gap between physical systems and digital spaces. We further leverage the federated learning to construct digital twin models of IoT devices based on their running data. Moreover, to mitigate the communication overhead, we propose an asynchronous model update scheme and formulate the federated learning scheme as an optimization problem. We further decompose the problem and solve the subproblems based on the deep neural network model. Numerical results show that our proposed federated learning scheme for DITEN improves the communication efficiency and reduces the transmission energy cost.},
	author = {Lu, Yunlong and Huang, Xiaohong and Zhang, Ke and Maharjan, Sabita and Zhang, Yan}
}
@article {28076,
	title = {Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {17},
	year = {2021},
	month = {07/2021},
	publisher = { IEEE},
	abstract = {The rapid development of industrial Internet of Things (IIoT) requires industrial production towards digitalization to improve network efficiency. Digital Twin is a promising technology to empower the digital transformation of IIoT by creating virtual models of physical objects. However, the provision of network efficiency in IIoT is very challenging due to resource-constrained devices, stochastic tasks, and resources heterogeneity. Distributed resources in IIoT networks can be efficiently exploited through computation offloading to reduce energy consumption while enhancing data processing efficiency. In this article, we first propose a new paradigm digital twin network to build network topology and the stochastic task arrival model in IIoT systems. Then, we formulate the stochastic computation offloading and resource allocation problem to minimize the long-term energy efficiency. As the formulated problem is a stochastic programming problem, we leverage Lyapunov optimization technique to transform the original problem into a deterministic per-time slot problem. Finally, we present asynchronous actor-critic algorithm to find the optimal stochastic computation offloading policy. Illustrative results demonstrate that our proposed scheme is able to significantly outperforms the benchmarks.},
	author = {Dai, Yueyue and Zhang, Ke and Maharjan, Sabita and Zhang, Yan}
}
@article {28077,
	title = {Digital Twin Empowered Content Caching in Social-aware Vehicular Edge Networks},
	journal = {IEEE Transactions on Computational Social Systems},
	volume = {9},
	year = {2021},
	month = {04/2021},
	pages = {239-251},
	publisher = { IEEE},
	abstract = {The rapid proliferation of smart vehicles along with the advent of powerful applications bring stringent requirements on massive content delivery. Although vehicular edge caching can facilitate delay-bounded content transmission, constrained storage capacity and limited serving range of an individual cache server as well as highly dynamic topology of vehicular networks may degrade the efficiency of content delivery. To address the problem, in this article, we propose a social-aware vehicular edge caching mechanism that dynamically orchestrates the cache capability of roadside units (RSUs) and smart vehicles according to user preference similarity and service availability. Furthermore, catering to the complexity and variability of vehicular social characteristics, we leverage the digital twin technology to map the edge caching system into virtual space, which facilitates constructing the social relation model. Based on the social model, a new concept of vehicular cache cloud is developed to incorporate the correlation of content storing between multiple cache-enabled vehicles in diverse traffic environments. Then, we propose deep learning empowered optimal caching schemes, jointly considering the social model construction, cache cloud formation, and cache resource allocation. We evaluate the proposed schemes based on real traffic data. Numerical results demonstrate that our edge caching schemes have great advantages in optimizing caching utility.},
	doi = {10.1109/TCSS.2021.3068369},
	author = {Zhang, Ke and Cao, Jiayu and Maharjan, Sabita and Zhang, Yan}
}
@article {28071,
	title = {Federated Learning empowered End-Edge-Cloud Cooperation for 5G HetNet Security},
	journal = {IEEE Network},
	volume = {35},
	year = {2021},
	month = {03/2021},
	pages = {88-94},
	publisher = { IEEE},
	abstract = {The distributed and heterogeneous framework in the 5G heterogeneous network (Het-Net) makes it vulnerable to attacks of different kinds. Nodes for improving the network security are therefore important to eliminate such critical threats. Without cooperation or with limited cooperation, these nodes are substantially restricted in their protecting capacity due to specific characteristics such as heterogeneity, hierarchy, and wide range in the 5G HetNet. In this article, we propose a federated learning empowered end-edge-cloud cooperation-based framework for enhancing 5G HetNet security. In this framework, nodes equipped with attack detection mechanisms are distributed in the end, edge, and cloud of the 5G HetNet. We then design cooperative training schemes to realize the full potential of these nodes in detecting attacks. Illustrative results demonstrate the superior performance of our proposed scheme compared to three different benchmark schemes.},
	author = {Wei, Yunkai and Zhou, Sipei and Leng, Supeng and Maharjan, Sabita and Zhang, Yan}
}
@article {28075,
	title = {Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {17},
	year = {2021},
	month = {07/2021},
	pages = {5098-5107},
	publisher = { IEEE},
	abstract = {Emerging technologies, such as digital twins and 6th generation (6G) mobile networks, have accelerated the realization of edge intelligence in industrial Internet of Things (IIoT). The integration of digital twin and 6G bridges the physical system with digital space and enables robust instant wireless connectivity. With increasing concerns on data privacy, federated learning has been regarded as a promising solution for deploying distributed data processing and learning in wireless networks. However, unreliable communication channels, limited resources, and lack of trust among users hinder the effective application of federated learning in IIoT. In this article, we introduce the digital twin wireless networks (DTWN) by incorporating digital twins into wireless networks, to migrate real-time data processing and computation to the edge plane. Then, we propose a blockchain empowered federated learning framework running in the DTWN for collaborative computing, which improves the reliability and security of the system and enhances data privacy. Moreover, to balance the learning accuracy and time cost of the proposed scheme, we formulate an optimization problem for edge association by jointly considering digital twin association, training data batch size, and bandwidth allocation. We exploit multiagent reinforcement learning to find an optimal solution to the problem. Numerical results on real-world dataset show that the proposed scheme yields improved efficiency and reduced cost compared to benchmark learning methods.},
	doi = {10.1109/TII.2020.3017668},
	author = {Lu, Yunlong and Huang, Xiaohong and Zhang, Ke and Maharjan, Sabita and Zhang, Yan}
}
@article {28073,
	title = {Mitigating Conflicting Transactions in Hyperledger Fabric Permissioned Blockchain for Delay-sensitive IoT Applications},
	journal = {IEEE Internet of Things Journal},
	volume = {8},
	year = {2021},
	month = {07/2021},
	pages = {10596-10607},
	publisher = {IEEE},
	abstract = {Blockchain is a promising emerging technology that is envisioned to play a key role in establishing secure and reliable Internet-of-Things (IoT) ecosystems without the involvement of any third party. Hyperledger Fabric, a permissioned blockchain system that can yield high throughput and low consensus delay, has shown its capability in enhancing security and privacy protection for delay-sensitive IoT services. The literature, however, has not considered the conflicting transaction problem which may substantially limit the system performance and degrade QoS for the end users. In this article, we propose CATP-Fabric, a new blockchain system to address the conflicting transaction problem by reducing the number of potentially conflicting transactions with less overhead. First, the transactions within a block are divided into different groups to facilitate parallel transaction processing. Then, CATP-Fabric filters stale transactions and prioritizes the read-only transactions in each group to eliminate unnecessary overhead. Finally, we formulate the selection of aborting transactions in CATP-Fabric as a binary integer-programming problem and develop a low-complexity optimization algorithm to minimize the number of aborted transactions. Illustrative results show that our proposed CATP-Fabric blockchain system achieves high throughput of successful transactions while maintaining a lower aborting transaction rate compared to the benchmark blockchain systems.},
	doi = {10.1109/JIOT.2021.3050244},
	author = {Xu, Xiaoqiong and Wang, Xiaonan and Li, Zonghang and Yu, Hongfang and Sun, Gang and Maharjan, Sabita and Zhang, Yan}
}
@article {28079,
	title = {Multi-Agent Deep Reinforcement Learning for Computation Offloading and Interference Coordination in Small Cell Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {70},
	year = {2021},
	month = {09/2021},
	pages = {9282-9293},
	publisher = { IEEE},
	abstract = {Integrating mobile edge computing (MEC) with small cell networks has been conceived as a promising solution to provide pervasive computing services. However, the interactions among small cells due to inter-cell interference, the diverse application-specific requirements, as well as the highly dynamic wireless environment make it challenging to design an optimal computation offloading scheme. In this paper, we focus on the joint design of computation offloading and interference coordination for edge intelligence empowered small cell networks. To this end, we propose a distributed multi-agent deep reinforcement learning (DRL) scheme with the objective of minimizing the overall energy consumption while ensuring the latency requirements. Specifically, we exploit the collaboration among small cell base station (SBS) agents to adaptively adjust their strategies, considering computation offloading, channel allocation, power control, and computation resource allocation. Further, to decrease the computation complexity and signaling overhead of the training process, we design a federated DRL scheme which only requires SBS agents to share their model parameters instead of local training data. Numerical results demonstrate that our proposed schemes can significantly reduce the energy consumption and effectively guarantee the latency requirements compared with the benchmark schemes.},
	doi = {10.1109/TVT.2021.3096928},
	author = {Huang, Xiaoyan and Leng, Supeng and Maharjan, Sabita and Zhang, Yan}
}
@article {28080,
	title = {Optimal Energy Trading with Demand Responses in Cloud Computing Enabled Virtual Power Plant in Smart Grids},
	journal = {IEEE Transactions on Cloud Computing},
	year = {2021},
	month = {10/2021},
	publisher = { IEEE},
	abstract = {The increasing penetration of renewable energy sources and electric vehicles (EVs) poses a significant challenge for the power grid operator in terms of increasing peak load and power quality reduction. Moreover, there is a growing demand for fast charging services in smart grids. Addressing the growing demand from fast charging services is challenging. To overcome this challenge, in this paper, we propose a new computational architecture combining energy trading and demand responses based on cloud computing for managing virtual power plants (VPPs) in smart grids. In the proposed system, EVs can be charged at high charging rates without affecting the operation of the power grid by purchasing energy through the energy trading platform in the cloud. In addition, users with storage devices can sell energy surplus to the market. On the one hand, the energy trading platform can be regarded as an internal market of the VPP that aims to maximize its revenue. The interest of the EV owners, on the other hand, is to minimize the cost for charging. Therefore, we model the interactions between the EV owners and the VPP as a non-cooperative game.},
	doi = {10.1109/TCC.2021.3118563},
	author = {Chung, Hwei-Ming and Maharjan, Sabita and Zhang, Yan and Eliassen, Frank and Strunz, Kai}
}
@article {28072,
	title = {Placement and Routing Optimization for Automated Inspection with UAVs: A Study in Offshore Wind Farm},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {17},
	year = {2021},
	month = {05/2021},
	pages = {3032-3043},
	publisher = { IEEE},
	abstract = {Wind power is a clean and widely deployed alternative to reducing our dependence on fossil fuel power generation. Under this trend, more turbines will be installed in wind farms. However, the inspection of the turbines in an offshore wind farm is a challenging task because of the harsh environment (e.g., rough sea, strong wind, and so on) that leads to high risk for workers who need to work at considerable height. Also, inspecting increasing number of turbines requires long man hours. In this regard, unmanned aerial vehicles (UAVs) can play an important role for automated inspection of the turbines for the operator, thus reducing the inspection time, man hours, and correspondingly the risk for the workers. In this case, the optimal number of UAVs enough to inspect all turbines in the wind farm is a crucial parameter. In addition, finding the optimal path for the UAVs{\textquoteright} routes for inspection is also important and is equally challenging. In this paper, we formulate a placement optimization problem to minimize the number of UAVs in the wind farm and a routing optimization problem to minimize the inspection time. Wind has an impact on the flying range and the flying speed of UAVs, which is taken into account for both problems. The formulated problems are NP-hard. We therefore design heuristic algorithms to find solutions to both problems, and then analyze the complexity of the proposed algorithms. The data of the Walney wind farm are then utilized to evaluate the performance of the proposed algorithms. Simulation results clearly show that the proposed methods can obtain the optimal routing path for UAVs during the inspection.},
	doi = {10.1109/TII.2020.3004816},
	author = {Chung, Hwei-Ming and Maharjan, Sabita and Zhang, Yan and Eliassen, Frank and Strunz, Kai}
}
@article {27386,
	title = {Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	year = {2020},
	pages = {4298 - 4311},
	publisher = { IEEE},
	abstract = {In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can improve the driving experience and service quality. However, the bandwidth, security and privacy issues hinder data providers from participating in the data sharing process. In addition, due to the intermittent and unreliable communications in IoV, the reliability and efficiency of data sharing need to be further enhanced. In this paper, we propose a new architecture based on federated learning to relieve transmission load and address privacy concerns of providers. To enhance the security and reliability of model parameters, we develop a hybrid blockchain architecture which consists of the permissioned blockchain and the local Directed Acyclic Graph (DAG). Moreover, we propose an asynchronous federated learning scheme by adopting Deep Reinforcement Learning (DRL) for node selection to improve the efficiency. The reliability of shared data is also guaranteed by integrating learned models into blockchain and executing a two-stage verification. Numerical results show that the proposed data sharing scheme provides both higher learning accuracy and faster convergence.},
	author = {Lu, Y. and Huang, X. and Zhang, K. and Maharjan, Sabita and Zhang, Yan}
}
@article {27385,
	title = {Deep Reinforcement Learning and Permissioned Blockchain for Content Caching in Vehicular Edge Computing and Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	year = {2020},
	month = {02/2020},
	pages = { 4312 - 4324},
	publisher = { IEEE},
	abstract = {Vehicular Edge Computing (VEC) is a promising paradigm to enable huge amount of data and multimedia content to be cached in proximity to vehicles. However, high mobility of vehicles and dynamic wireless channel condition make it challenge to design an optimal content caching policy. Further, with much sensitive personal information, vehicles may be not willing to caching their contents to an untrusted caching provider. Deep Reinforcement Learning (DRL) is an emerging technique to solve the problem with high-dimensional and time-varying features. Permission blockchain is able to establish a secure and decentralized peer-to-peer transaction environment. In this paper, we integrate DRL and permissioned blockchain into vehicular networks for intelligent and secure content caching. We first propose a blockchain empowered distributed content caching framework where vehicles perform content caching and base stations maintain the permissioned blockchain. Then, we exploit the advanced DRL approach to design an optimal content caching scheme with taking mobility into account. Finally, we propose a new block verifier selection method, Proof-of-Utility (PoU), to accelerate block verification process. Security analysis shows that our proposed blockchain empowered content caching can achieve security and privacy protection. Numerical results based on a real dataset from Uber indicate that the DRL-inspired content caching scheme significantly outperforms two benchmark policies.},
	author = {Dai, Y. and Xu, D. and Zhang, K. and Maharjan, Sabita and Zhang, Yan}
}
@article {27378,
	title = {Deep Reinforcement Learning for Cooperative Content Caching in Vehicular Edge Computing and Networks},
	journal = {IEEE Internet of Things Journal},
	volume = {7},
	year = {2020},
	month = {01/2020},
	pages = {247-257},
	publisher = { IEEE},
	abstract = {In this article, we propose a cooperative edge caching scheme, a new paradigm to jointly optimize the content placement and content delivery in the vehicular edge computing and networks, with the aid of the flexible trilateral cooperations among a macro-cell station, roadside units, and smart vehicles. We formulate the joint optimization problem as a double time-scale Markov decision process (DTS-MDP), based on the fact that the time-scale of content timeliness changes less frequently as compared to the vehicle mobility and network states during the content delivery process. At the beginning of the large time-scale, the content placement/updating decision can be obtained according to the content popularity, vehicle driving paths, and resource availability. On the small time-scale, the joint vehicle scheduling and bandwidth allocation scheme is designed to minimize the content access cost while satisfying the constraint on content delivery latency. To solve the long-term mixed integer linear programming (LT-MILP) problem, we propose a nature-inspired method based on the deep deterministic policy gradient (DDPG) framework to obtain a suboptimal solution with a low computation complexity. The simulation results demonstrate that the proposed cooperative caching system can reduce the system cost, as well as the content delivery latency, and improve content hit ratio, as compared to the noncooperative and random edge caching schemes.},
	doi = { 10.1109/JIOT.2019.2945640},
	url = {https://ieeexplore.ieee.org/abstract/document/8879573},
	author = {Qiao, G. and Leng, Supeng and Maharjan, Sabita and Zhang, Yan and Ansari, Nirwan}
}
@article {27381,
	title = {Deep Reinforcement Learning for Social-Aware Edge Computing and Caching in Urban Informatics},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {16},
	year = {2020},
	pages = {5467 - 5477},
	publisher = { IEEE},
	abstract = {Empowered with urban informatics, transportation industry has witnessed a paradigm shift. These developments lead to the need of content processing and sharing between vehicles under strict delay constraints. Mobile edge services can help meet these demands through computation offloading and edge caching empowered transmission, while cache-enabled smart vehicles may also work as carriers for content dispatch. However, diverse capacities of edge servers and smart vehicles, as well as unpredictable vehicle routes, make efficient content distribution a challenge. To cope with this challenge, in this article we develop a social-aware nobile edge computing and caching mechanism by exploiting the relation between vehicles and roadside units. By leveraging a deep reinforcement learning approach, we propose optimal content processing and caching schemes that maximize the dispatch utility in an urban environment with diverse vehicular social characteristics.},
	author = {Zhang, K. and Cao, J. and Liu, H. and Maharjan, Sabita and Zhang, Yan}
}
@article {27379,
	title = {Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatics},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {16},
	year = {2020},
	month = {03/2020},
	pages = {2134 - 2143},
	publisher = { IEEE},
	abstract = {Driven by technologies such as mobile edge computing and 5G, recent years have witnessed the rapid development of urban informatics, where a large amount of data is generated. To cope with the growing data, artificial intelligence algorithms have been widely exploited. Federated learning is a promising paradigm for distributed edge computing, which enables edge nodes to train models locally without transmitting their data to a server. However, the security and privacy concerns of federated learning hinder its wide deployment in urban applications such as vehicular networks. In this article, we propose a differentially private asynchronous federated learning scheme for resource sharing in vehicular networks. To build a secure and robust federated learning scheme, we incorporate local differential privacy into federated learning for protecting the privacy of updated local models. We further propose a random distributed update scheme to get rid of the security threats led by a centralized curator. Moreover, we perform the convergence boosting in our proposed scheme by updates verification and weighted aggregation. We evaluate our scheme on three real-world datasets. Numerical results show the high accuracy and efficiency of our proposed scheme, whereas preserve the data privacy.},
	issn = {Print ISSN: 1551-3203 Electronic ISSN: 1941-0050},
	doi = {10.1109/TII.2019.2942179},
	url = {https://ieeexplore.ieee.org/document/8843942/authors$\#$authors},
	author = {Lu, Y. and Huang, X. and Dai, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {28069,
	title = {Distributed Deep Reinforcement Learning for Intelligent Load Scheduling in Residential Smart Grid},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {17},
	year = {2020},
	month = {04/2020},
	publisher = { IEEE},
	abstract = {The power consumption of households has been constantly growing over the years. To cope with this growth, intelligent management of the consumption profile of the households is necessary, such that the households can save the electricity bills, and the stress to the power grid during peak hours can be reduced. However, implementing such a method is challenging due to the existence of randomness in the electricity price and the consumption of the appliances. To address this challenge, we employ a model-free method for the households which works with limited information about the uncertain factors. More specifically, the interactions between households and the power grid can be modeled as a non-cooperative stochastic game, where the electricity price is viewed as a stochastic variable. To search for the Nash equilibrium (NE) of the game, we adopt a method based on distributed deep reinforcement learning. Also, the proposed method can preserve the privacy of the households. We then utilize real-world data from Pecan Street Inc., which contains the power consumption profile of more than 1; 000 households, to evaluate the performance of the proposed method. In average, the results reveal that we can achieve around 12\% reduction on peak-to-average ratio (PAR) and 11\% reduction on load variance. With this approach, the operation cost of the power grid and the electricity cost of the households can be reduced.},
	author = {Chung, Hwei-Ming and Maharjan, Sabita and Zhang, Yan and Eliassen, Frank}
}
@inproceedings {28082,
	title = {Edge Intelligence Empowered UAV s for Automated Wind Farm Monitoring in Smart Grids},
	journal = {IEEE Globecom 2020},
	year = {2020},
	publisher = { IEEE},
	abstract = {With the exploitation of wind power, more turbines will be deployed at remote areas possibly with harsh working conditions (e.g., offshore wind farm). The adverse working environment may lead to massive operating and maintenance costs of turbines. Deploying unmanned aerial vehicles (UAVs) for turbine inspection is considered as a viable alternative to manual inspections. An important objective of automated UAV inspection is to minimize the flight time of the UAVs to inspect all the turbines. A first contribution of this paper is thus formulating an optimization problem to compute the optimal routes for turbine inspection satisfying the above goal. On the other hand, the limited computational capability on UAVs can be used to increase the power generation of wind turbine. Power generation from the turbines can be optimized by controlling the yaw angle of the turbines. Forecasting wind conditions such as wind speed and wind direction is crucial for solving both optimization problems. Therefore, UAVs can utilize their limited computational capability to perform wind forecasting. In this way, UAVs form edge intelligence in offshore wind farm. With the forecasted wind conditions, we design two algorithms to solve the formulated problems, and then evaluate the proposed methods with real-world data. The results reveal that the proposed methods offer an improvement of 44\% of the power generation from the turbine compared to hour-ahead forecasting and 25\% reduction of the flight time of the UAVs compared to the chosen baseline method.},
	doi = {10.1109/GLOBECOM42002.2020.9322269},
	author = {Chung, Hwei-Ming and Maharjan, Sabita and Zhang, Yan and Eliassen, Frank and Yuan, Tingting}
}
@article {28067,
	title = {Edge Intelligence for Energy-efficient Computation Offloading and Resource Allocation in 5G Beyond},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	year = {2020},
	month = {10/2020},
	publisher = { IEEE},
	abstract = {5G beyond is an end-edge-cloud orchestrated network that can exploit heterogeneous capabilities of the end devices, edge servers, and the cloud and thus has the potential to enable computation-intensive and delay-sensitive applications via computation offloading. However, in multi user wireless networks, diverse application requirements and the possibility of various radio access modes for communication among devices make it challenging to design an optimal computation offloading scheme. In addition, having access to complete network information that includes variables such as wireless channel state, available bandwidth and computation resources, is a major issue. Deep Reinforcement Learning (DRL) is an emerging technique to address such an issue with limited and less accurate network information. In this paper, we utilize DRL to design an optimal computation offloading and resource allocation strategy for minimizing system energy consumption. We first present a multi-user end-edge-cloud orchestrated network where all devices and base stations have computation capabilities. Then, we formulate the joint computation offloading and resource allocation problem as a Markov Decision Process (MDP) and propose a new DRL algorithm to minimize system energy consumption. Numerical results based on a real-world dataset demonstrate that the proposed DRL-based algorithm significantly outperforms the benchmark policies in terms of system energy consumption. Extensive simulations show that learning rate, discount factor, and number of devices have considerable influence on the performance of the proposed algorithm.},
	author = {Dai, Yueyue and Zhang, Ke and Maharjan, Sabita and Zhang, Yan}
}
@article {27383,
	title = {Energy Efficiency and Delay Tradeoff for Wireless Powered Mobile-Edge Computing Systems with Multi-Access Schemes},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {9},
	year = {2020},
	pages = {1855 - 1867},
	publisher = { IEEE},
	abstract = {The integration of Mobile-edge Computing (MEC) and Wireless Energy Transfer (WET) has been recognized as a promising technique to enhance computation capability and to prolong battery lifetime of resource-constrained wireless devices in the Internet of Things (IoT) era. However, it is challenging to jointly schedule energy, radio, and computational resources for coordinating heterogeneous performance requirements in wireless powered MEC systems. To fill this gap, this paper investigates the fundamental tradeoff between Energy Efficiency (EE) and delay in a multi-user wireless powered MEC system. Considering the random channel conditions and task arrivals, we formulate a stochastic optimization problem to study the EE-delay tradeoff, which optimizes network EE subject to network stability, maximum central processing unit frequency, peak transmission power, available communication resource, and energy causality constraints. Further, we propose the online computation offloading and resource allocation algorithm by transforming the original problem into a series of deterministic optimization problems in each time block based on Lyapunov optimization theory. In addition, theoretical analysis shows that the algorithm achieves the EE-delay tradeoff as [O(1/V), O(V)] and introduces a control parameter V to balance the EE-delay performance. Numerical results verify the theoretical analysis and reveal the impact of various parameters to the system performance.},
	author = {Mao, S. and Leng, Supeng and Maharjan, Sabita and Zhang, Yan}
}
@article {27380,
	title = {Federated Learning for Data Privacy Preservation in Vehicular Cyber-Physical Systems},
	journal = {IEEE Network},
	volume = {34},
	year = {2020},
	month = {05/2020},
	pages = {50-56},
	publisher = { IEEE},
	abstract = {Recent developments in technologies such as MEC and AI contribute significantly in accelerating the deployment of VCPS. Techniques such as dynamic content caching, efficient resource allocation, and data sharing play a crucial role in enhancing the service quality and user driving experience. Meanwhile, data leakage in VCPS can lead to physical consequences such as endangering passenger safety and privacy, and causing severe property loss for data providers. The increasing volume of data, the dynamic network topology, and the availability of limited resources make data leakage in VCPS an even more challenging problem, especially when it involves multiple users and multiple transmission channels. In this article, we first propose a secure and intelligent architecture for enhancing data privacy. Then we present our new privacy-preserving federated learning mechanism and design a two-phase mitigating scheme consisting of intelligent data transformation and collaborative data leakage detection. Numerical results based on a real-world dataset demonstrate the effectiveness of our proposed scheme and show that our scheme achieves good accuracy, efficiency, and high security.},
	issn = {Print ISSN: 0890-8044 Electronic ISSN: 1558-156X},
	doi = {10.1109/MNET.011.1900317},
	url = {https://ieeexplore.ieee.org/document/9105934},
	author = {Lu, Y. and Huang, X. and Dai, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {28068,
	title = {Incentivizing Resource Cooperation for Blockchain Empowered Wireless Power Transfer in UAV Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	year = {2020},
	month = {12/2020},
	publisher = { IEEE},
	abstract = {In unmanned aerial vehicle (UAV) networks, UAVs-assisted wireless power transfer is a promising approach to charge low-power smart devices for energy replenishment. However, security and privacy concerns associated with the energy micro-transactions in untrusted wireless trading environment present serious challenges. In this paper, we exploit Directed Acyclic Graph (DAG) and consortium blockchain to propose a new distributed and secure UAVs-assisted wireless power transfer framework named aerial-ground chain, where heterogeneous consensus is developed to verify the energy micro-transactions. Specifically, the UAVs verify energy micro-transactions simultaneously but asynchronously to form an aerial tangle. The smart devices also participate in maintaining the aerial tangle. We define timeout for the energy micro-transactions, and leverage a set of Access Points (APs) to cooperatively confirm the timeout energy micro-transaction by utilizing consortium blockchain, to form a ground main chain. Furthermore, a contract theory based resource cooperation scheme is designed to motivate the UAVs to participate in wireless power transfer, and to incentivize the APs to contribute their resources in cooperatively verifying the timeout energy micro-transactions. Security analysis and numerical results illustrate that the developed aerial-ground chain and the designed contract theory based resource cooperation scheme are secure and efficient for UAVs-assisted wireless power transfer.},
	author = {Jiang, Li and Chen, Bin and Xie, Shengli and Maharjan, Sabita and Zhang, Yan}
}
@article {28066,
	title = {Intelligent Charging Management of Electric Vehicles Considering Dynamic User Behavior and Renewable Energy: A Stochastic Game Approach},
	journal = { IEEE Transactions on Intelligent Transportation Systems},
	year = {2020},
	month = {07/2020},
	publisher = { IEEE},
	abstract = {Uncoordinated charging of a rapidly growing number of electric vehicles (EVs) and the uncertainty associated with renewable energy resources may constitute a critical issue for the electric mobility (E-Mobility) in the transportation system especially during peak hours. To overcome this dire scenario, we introduce a stochastic game to study the complex interactions between the power grid and charging stations. In this context, existing studies have not taken into account the dynamics of customers{\textquoteright} preference on charging parameters. In reality, however, the choice of the charging parameters may vary over time, as the customers may change their charging preferences. We model this behavior of customers with another stochastic game. Moreover, we define a quality of service (QoS) index to reflect how the charging process influences customers{\textquoteright} choices on charging parameters. We also develop an online algorithm to reach the Nash equilibria for both stochastic games. Then, we utilize real data from the California Independent System Operator (CAISO) to evaluate the performance of our proposed algorithms. The results reveal that the electricity cost with the proposed method can result in a saving of about 20\% compared to the benchmark method, while also yielding a higher QoS in terms of charging and waiting time. Our results can be employed as guidelines for charging service providers to make efficient decisions under uncertainty relative to power generation of renewable energy.},
	doi = {10.1109/TITS.2020.3008279},
	author = {Chung, Hwei-Ming and Maharjan, Sabita and Zhang, Yan and Eliassen, Frank}
}
@article {27382,
	title = {Joint Transaction Relaying and Block Verification Optimization for Blockchain Empowered D2D Communication},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {69},
	year = {2020},
	pages = {828 - 841},
	publisher = { IEEE},
	abstract = {Device to device (D2D) communication is a promising paradigm to support data sharing in the fifth generation (5G) small cell networks. However, D2D communication is more vulnerable to security and privacy threats due to direct wireless connection between the proximity devices. In this paper, we exploit blockchain technology to propose a new distributed and secure data sharing framework named D2D blockchain, where we deploy a set of Access Points (APs) to verify end users{\textquoteright} transactions. Besides, in order to enable the end users to receive the required data on time in the D2D blockchain, we propose two new schemes for the transaction confirmation procedure including a relay-assisted transaction relaying scheme and a Delegated Proof-of-Stake (DPoS) based lightweight block verification scheme. Furthermore, to incentivize the relay devices to help in relaying transactions in congested areas, and to encourage the verifiers to contribute their resources in block verification, we design a two-stage contract theory based joint optimization scheme. To measure the quality of the relayed transaction and the verified block, we formulate two models: value of transaction relaying (VoTR) and value of block verification (VoBV), and then design the optimal contract for each relay device and each verifier. Security analysis and numerical results illustrate that the proposed D2D blockchain and the designed joint optimization scheme are secure and efficient for data sharing among end users.},
	author = {Jiang, L. and Xie, S. and Maharjan, Sabita and Zhang, Yan}
}
@article {28065,
	title = {Protecting Machine Learning Integrity in Distributed Big Data Networking},
	journal = {IEEE Network},
	volume = {34},
	year = {2020},
	month = {07/2020},
	publisher = { IEEE},
	abstract = {A distributed big data network is the integration of big data and the underlying distributed network. This emerging paradigm brings the potential to divide big data processing tasks into smaller ones so that they can be intelligently processed in parallel with machine learning based on distributed network resources. Such a pattern requires strict system integrity, especially machine learning integrity against data tampering or network control by malicious nodes. In this article, we propose a secure architecture consisting of one HaSi scheme and two data tampering detection schemes for protecting the machine learning integrity in distributed big data networking. Illustrative results demonstrate the effect of our proposed schemes, and show that they can ensure the learning accuracy even when 30-40 percent of processing nodes are maliciously controlled. When the figure raises to 40-50 percent, the accuracy of our proposed schemes begins to fall visibly, but still outperforms the scenario without protection by up to 70-80 percent.},
	author = {Wei, Yunkai and Chen, Yijin and Xiao, Mingyue and Maharjan, Sabita and Zhang, Yan}
}
@article {26443,
	title = {Artificial Intelligence Empowered Edge Computing and Caching for Internet of Vehicles},
	journal = {IEEE Wireless Communications Magazine},
	volume = {26},
	year = {2019},
	pages = {12-18},
	publisher = {IEEE},
	abstract = {Recent advances in edge computing and caching have significant impacts on the developments of vehicular networks. Nevertheless, the heterogeneous requirements of onvehicle applications and the time-variability on popularity of contents, bring great challenges for edge servers to efficiently utilize their resources. Moreover, the high mobility of smart vehicles adds substantial complexity in jointly optimizing edge computing and caching. Artificial Intelligence (AI) can greatly enhance the cognition and intelligence of vehicular networks and thus assist in optimally allocating resources for the problems with diverse, time-variant, and complex features. In this article, we propose a new architecture that can dynamically orchestrate edge computing and caching resources to improve system utility by making full use of AI based algorithms. Then we formulate a joint edge computing and caching scheme to maximize system utility and develop a novel resource scheme by exploiting deep reinforcement learning. Numerical results demonstrate the effectiveness of the proposed scheme.},
	author = {Dai, Y. and Xu, D. and Maharjan, Sabita and Zhang, Yan}
}
@article {26444,
	title = {Artificial Intelligence Empowered Mobile Sensing for Human Flow Detection},
	journal = {IEEE Network Magazine},
	volume = {33},
	year = {2019},
	month = {02/2019},
	pages = {78-83},
	publisher = {IEEE},
	abstract = {Intelligent human detection based on WiFi is a technique that has recently attracted a significant amount of interest from research communities. The use of ubiquitous WiFi to detect the number of queuing persons can facilitate dynamic planning and appropriate service provisioning. In this article, we propose HFD, one of the first schemes to leverage WiFi signals to estimate the number of queuing persons by employing classifiers from machine learning in a device-free manner. In the proposed HFD scheme, we first utilize the sliding window method to filter and remove the outliers. We extract two characteristics, skewness and kurtosis, as the identification features. Then, we use the support vector machine (SVM) to classify these two features to estimate the number of people in the current queue. Finally, we combine our scheme with the latest Fresnel Zone model theory to determine whether someone is in or out, and thus dynamically adjust the detected value. We implement a proof-of-concept prototype upon commercial WiFi devices and evaluate it in both conference room and corridor scenarios. The experimental results show that the accuracy of our proposed HFD detection can be maintained at about 90 percent with high robustness.},
	author = {Xiao, F. and Guo, Z. and Ni, Y. and Xie, X. and Maharjan, Sabita and Zhang, Yan}
}
@article {26973,
	title = {Blockchain and Deep Reinforcement Learning Empowered Intelligent 5G Beyond},
	journal = {IEEE Network},
	volume = {33},
	number = {10-17},
	year = {2019},
	month = {05/2019},
	publisher = {IEEE},
	abstract = {Blockchain and AI are promising techniques for next-generation wireless networks. Blockchain can establish a secure and decentralized resource sharing environment. AI can be explored to solve problems with uncertain, time-variant, and complex features. Both of these techniques have recently seen a surge in interest. The integration of these two techniques can further enhance the performance of wireless networks. In this article, we first propose a secure and intelligent architecture for next generation wireless networks by integrating AI and blockchain into wireless networks to enable flexible and secure resource sharing. Then we propose a blockchain empowered content caching problem to maximize system utility, and develop a new caching scheme by utilizing deep reinforcement learning. Numerical results demonstrate the effectiveness of the proposed scheme.},
	author = {Dai, Y. and Xu, D. and Maharjan, Sabita and Chen, Z. and He, Q. and Zhang, Yan}
}
@article {26979,
	title = {Blockchain and Federated Learning for Privacy-preserved Data Sharing in Industrial IoT},
	journal = { IEEE Transactions on Industrial Informatics (Early Access)},
	year = {2019},
	publisher = { IEEE},
	abstract = {The rapid increase in the volume of data generated from connected devices in Industrial Internet of Things (IIoT) paradigm, opens up new possibilities for enhancing the quality of service for the emerging applications through data sharing. However, security and privacy concerns (e.g, data leakage) are major obstacles for data providers to share their data in wireless networks. The leakage of private data can lead to serious issues beyond financial loss for the providers. In this article, we first propose a blockchain empowered secure data sharing architecture for distributed multiple parties. Then, we transfer the data sharing problem into a machine learning problem by incorporating privacy-preserved federated learning. The privacy of data is well maintained by sharing the data model instead of revealing the actual data. Finally, we integrate federated learning in the consensus process of permissioned blockchain thus the computing work for consensus can also be used for federated training. Numerical results derived from real-world datasets show that the proposed data sharing scheme achieves good accuracy, high efficiency and enhanced security.},
	author = {Lu, Y. and Huang, X. and Dai, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {26975,
	title = {Blockchain Empowered Wireless Power Transfer for Green and Secure Internet of Things},
	journal = {IEEE Network},
	volume = {33},
	year = {2019},
	month = {09/2019},
	pages = {164-171},
	publisher = { IEEE},
	abstract = {Wireless power transfer is a promising approach to charge low-power IoT devices for energy replenishment. However, energy attacks from malicious IoT devices can result in significant energy loss to energy transmitters. In this article, we propose a new distributed and secure wireless power transfer architecture by utilizing blockchain. The proposed architecture includes two planes: the energy plane and blockchain plane. We further abstract three types of traffic flows, transaction flow, consensus flow and coin flow, to provide a profound insight into the workflow of blockchain. Furthermore, to obtain the optimal amount of transferred energy in the energy plane, and to resolve high operational overhead of the consensus process in the blockchain plane, we develop a contract theory based wireless power transfer scheme and a DPoS based lightweight consensus scheme, and design an efficient wireless power transfer mechanism by combining the two schemes. Illustrative results demonstrate that our proposed schemes offer significant energy loss reduction with moderate operational overhead.},
	author = {Jiang, L. and Xie, S. and Maharjan, Sabita and Zhang, Yan}
}
@article {26974,
	title = {Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics},
	journal = {IEEE Internet of Things Journal},
	volume = {6},
	number = {Oct 2019},
	year = {2019},
	month = {03/2019},
	publisher = { IEEE},
	abstract = {Led by industrialization of smart cities, numerous interconnected mobile devices, and novel applications have emerged in the urban environment, providing great opportunities to realize industrial automation. In this context, autonomous driving is an attractive issue, which leverages large amounts of sensory information for smart navigation while posing intensive computation demands on resource constrained vehicles. Mobile edge computing (MEC) is a potential solution to alleviate the heavy burden on the devices. However, varying states of multiple edge servers as well as a variety of vehicular offloading modes make efficient task offloading a challenge. To cope with this challenge, we adopt a deep Q-learning approach for designing optimal offloading schemes, jointly considering selection of target server and determination of data transmission mode. Furthermore, we propose an efficient redundant offloading algorithm to improve task offloading reliability in the case of vehicular data transmission failure. We evaluate the proposed schemes based on real traffic data. Results indicate that our offloading schemes have great advantages in optimizing system utilities and improving offloading reliability.},
	author = {Zhang, K. and Zhu, Y. and Leng, S. and He, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {26977,
	title = {Deep Learning for Secure Mobile Edge Computing in Cyber-Physical Transportation Systems},
	journal = {IEEE Network},
	volume = {33},
	year = {2019},
	month = {07/2019},
	pages = {36-41},
	publisher = { IEEE},
	abstract = {MEC is able to be used to execute the compute- intensive applications on the edge of transportation networks directly. As a result, the communications traffic is substantially increased among the connected edge devices. Therewith, communications security is emerging as a serious problem, and as an important research issue of the communications security, active feature learning is studied in this article for actively detecting unknown attacks. A model based on deep learning is designed to learn attack features. This model uses unsupervised learning to accomplish the active learning process. In the evaluation, 10 datasets are used to conduct experiments. We compare our model with four other machinelearning- based algorithms, and the comparative results illustrate that our model has a 6 percent gain in accuracy.},
	author = {Chen, Y. and Zhang, Yan and Maharjan, Sabita and Alam, M. and Wu, T.}
}
@inproceedings {26970,
	title = {Deep Reinforcement Learning for Edge Caching and Content Delivery in Internet of Vehicles},
	journal = {IEEE/CIC International Conference on Communications in China (ICCC)},
	year = {2019},
	publisher = {IEEE/CIC},
	abstract = {To enable the emerging vehicular applications and multimedia services in an Internet of Vehicles (IoV) framework, edge caching is a promising paradigm which can cache content in proximity to vehicles, and thus alleviate heavy load on backhaul links and contribute in reducing transmission latency. However, in a multi-access vehicular network, complex content delivery and high mobility of vehicles introduce new challenges to support edge caching in a dynamic environment. Deep Reinforcement Learning (DRL) is an emerging technique to solve the issue with time-varying feature. In this paper, we utilize DRL to design an optimal vehicular edge caching and content delivery strategy for minimizing content delivery latency. We first propose a multiaccess edge caching and content delivery framework in vehicular networks. Then, we formulate the vehicular edge caching and content delivery problem and propose a novel DRL algorithm to solve it. Numerical results demonstrate the effectiveness of proposed DRL-based algorithm, compared to two benchmark solutions.},
	author = {Dai, Y. and Xu, D. and Lu, Y. and Maharjan, Sabita and Zhang, Yan}
}
@inproceedings {26972,
	title = {Deep Reinforcement Learning for Edge Computing and Resource Allocation in 5G Beyond},
	journal = {2019 IEEE 19th International Conference on Communication Technology (ICCT)},
	year = {2019},
	pages = {866-870},
	publisher = { IEEE},
	abstract = {By extending computation capacity to the edge of wireless networks, edge computing has the potential to enable computation-intensive and delay-sensitive applications in 5G and beyond via computation offloading. However, in multi-user heterogeneous networks, it is challenging to capture complete network information, such as wireless channel state, available bandwidth or computation resources. The strong couplings among devices on application requirements or radio access mode make it more difficult to design an optimal computation offloading scheme. Deep Reinforcement Learning (DRL) is an emerging technique to address such an issue with limited and less accurate network information. In this paper, we utilize DRL to design an optimal computation offloading and resource allocation strategy for minimizing system energy consumption. We first present a multi-user edge computing framework in heterogeneous networks. Then, we formulate the joint computation offloading and resource allocation problem as a DRL form and propose a new DRL-inspired algorithm to minimize system energy consumption. Numerical results based on a realworld dataset demonstrate demonstrate the effectiveness of our proposed algorithm, compared to two benchmark solutions.},
	author = {Dai, Y. and Xu, D. and Zhang, K. and Lu, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {26340,
	title = {Distributed Uplink Offloading for IoT in 5G Heterogeneous Networks under Private Information Constraints},
	journal = {IEEE Internet of Things Journal},
	volume = {6},
	year = {2019},
	month = {12/2018},
	pages = {6151-6164},
	publisher = {IEEE},
	abstract = {The expected influx of Internet of Things (IoT) in 5G will provide new opportunities for uplink traffic offloading. In general, base stations with proximity require lower transmission power of the IoT device (IoTD), thus saving energy consumption as spectral efficiency (SE) of the transmissions increase. By letting IoTDs send to base stations with better link conditions the IoTDs{\textquoteright} battery lifetime is prolonged. In this work we present a many-to-many offloading scheme for uplink traffic. The scheme works when link conditions are private information and gives incentives to all involved players to participate. We believe this approach is better suited for the expected complex ecosystem of 5G base station cells. The sensitivity analyses show that there is a limited gain by requiring that the link conditions are public knowledge. Further, the suggested market optimizes the SE for all involved players. Numerical results show that the IoTDs can on average increase their SE with 25\% and their spectral energy efficiency with 40\%. The networks which are offloaded to and from can both expect an increase in the SE of 1\%-6\%. Sensitivity analyses show that the market equilibrium{\textquoteright}s benefits are robust as they stay positive for a range of different network configurations. Also, the work proves that market equilibrium is stable and unique. To derive the equilibrium, two approaches are presented, a closed form solution and a distributed algorithm, that both are solvable in polynomial time.\&nbsp;},
	doi = {10.1109/JIOT.2018.2886703},
	author = {Kure, Endre and Engelstad, Paal and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@article {26976,
	title = {Edge Intelligence and Blockchain Empowered 5G Beyond for Industrial Internet of Things},
	journal = {IEEE Network},
	volume = {33},
	number = {12-19},
	year = {2019},
	month = {10/2019},
	publisher = { IEEE},
	abstract = {Edge intelligence is a key enabler for IIoT as it offers smart cloud services in close proximity to the production environment with low latency and less cost. The need for ubiquitous communication, computing, and caching resources in 5G beyond will lead to a growing demand to integrate heterogeneous resources into the edge network. Furthermore, distributed edge services can make resource transactions vulnerable to malicious nodes. Ensuring secure edge services under complex industrial networks is a big challenge. In this article, we present an edge intelligence and blockchain empowered IIoT framework, which achieves flexible and secure edge service management. Then we propose a cross-domain sharing inspired edge resource scheduling scheme and design a credit-differentiated edge transaction approval mechanism. Numerical results indicate that the proposed schemes bring significant improvement in both edge service cost and service capacities.},
	author = {Zhang, K. and Zhu, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {26978,
	title = {Energy Peer-to-Peer Trading in Virtual Microgrids in Smart Grids: A Game-Theoretic Approach},
	journal = {IEEE Transactions on Smart Grid (Early Access)},
	year = {2019},
	month = {08/2019},
	publisher = { IEEE},
	abstract = {raditionally, energy consumers pay non-commodity charges (e.g. transmission, environmental and network costs) as a major component of their energy bills. With the distributed energy generation, enabling energy consumption close to producers can minimize such costs. The physically constrained energy prosumers in power networks can be logically grouped into virtual microgrids (VMGs) using communication systems. Prosumer benefits can be optimised by modelling the energy trading interactions among producers and consumers in a VMG as a Stackelberg game in which producers lead and consumers follow. Considering renewable (RES) and non-renewable energy (nRES) resources, and given that RES are unpredictable thus unschedulable, we also describe cost and utility models that include load uncertainty demands of producers. The results show that under Stackelberg equilibrium (SE), the costs incurred by a consumer for procuring either the RES or nRES are significantly reduced while the derived utility by producer is maximized. We further show that when the number of prosumers in the VMG increases, the CO2 emission cost and consequently the energy cost are minimized at the SE. Lastly, we evaluate the peer-to-peer (P2P) energy trading scenario involving noncooperative energy prosumers with and without Stackelberg game. The results show that the P2P energy prosumers attain 47\% higher benefits with Stackelberg game.},
	author = {Anoh, K. and Maharjan, Sabita and Ikpehai, A. and Zhang, Yan and Adebisi, B.}
}
@article {26439,
	title = {Artificial Intelligence Inspired Transmission Scheduling in Cognitive Vehicular Communications and Networks},
	journal = {IEEE Internet of Things Journal},
	year = {2018},
	month = {09/2018},
	publisher = {IEEE},
	abstract = {The Internet of things (IoT) platform has played a significant role in improving road transport safety and efficiency by ubiquitously connecting intelligent vehicles through wireless communications. Such an IoT paradigm however, brings in considerable strain on limited spectrum resources due to the need of continuous communication and monitoring. Cognitive radio (CR) is a potential approach to alleviate the spectrum scarcity problem through opportunistic exploitation of the underutilized spectrum. However, highly dynamic topology and time-varying spectrum states in CR-based vehicular networks introduce quite a few challenges to be addressed. Moreover, a variety of vehicular communication modes, such as vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V), as well as data QoS requirements pose critical issues on efficient transmission scheduling. Based on this motivation, in this paper, we adopt a deep Q-learning approach for designing an optimal data transmission scheduling scheme in cognitive vehicular networks to minimize transmission costs while also fully utilizing various communication modes and resources. Furthermore, we investigate the characteristics of communication modes and spectrum resources chosen by vehicles in different network states, and propose an efficient learning algorithm for obtaining the optimal scheduling strategies. Numerical results are presented to illustrate the performance of the proposed scheduling schemes.},
	doi = {10.1109/JIOT.2018.2872013},
	author = {Zhang, K. and Leng, S. and Peng, X. and Pan, L. and Maharjan, Sabita and Zhang, Yan}
}
@article {26440,
	title = {Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks},
	journal = {IEEE Internet of Things Journal},
	year = {2018},
	month = {10/2018},
	publisher = {IEEE},
	abstract = {The drastically increasing volume and the growing trend on the types of data have brought in the possibility of realizing advanced applications such as enhanced driving safety, and have enriched existing vehicular services through data sharing among vehicles and data analysis. Due to limited resource of vehicles, mobile edge computing integrated with vehicular networks gives rise to Vehicular Edge COmputing and Networks (VECONs) for providing powerful computing and massive storage resources. However, vehicular edge computing servers consisted of roadside units cannot be fully trusted, which may result in serious security and privacy challenges. We exploit consortium blockchain and smart contract technologies to achieve secure data storage and sharing in vehicular edge networks. These technologies efficiently prevent data sharing without authorization. In addition, we propose a reputation based data sharing scheme to ensure high-quality data sharing among vehicles. A three-weight subjective logic model is utilized for precisely managing reputation of the vehicles. Numerical results based on a real dataset show that our schemes achieve reasonable efficiency and high-level security for data sharing in VECONs.},
	author = {Kang, J. and Yu, R. and Huang, X. and Yu, M. and Maharjan, Sabita and Xie, S. and Zhang, Yan}
}
@article {25570,
	title = {Contract-theoretic Approach for Delay Constrained Offloading in Vehicular Edge Computing Networks},
	journal = {Mobile Networks and Applications},
	year = {2018},
	pages = {1-12},
	publisher = {Springer},
	address = {US},
	abstract = {Mobile Edge Computing (MEC) is a promising solution to improve vehicular services through offloading computation to cloud servers in close proximity to mobile vehicles. However, the self-interested nature together with the high mobility characteristic of the vehicles make the design of the computation offloading scheme a significant challenge. In this paper, we propose a new Vehicular Edge Computing (VEC) framework to model the computation offloading process of the mobile vehicles running on a bidirectional road. Based on this framework, we adopt a contract theoretic approach to design optimal offloading strategies for the VEC service provider, which maximize the revenue of the provider while enhancing the utilities of the vehicles. To further improve the utilization of the computing resources of the VEC servers, we incorporate task priority distinction as well as additional resource providing into the design of the offloading scheme, and propose an efficient VEC server selection and computing resource allocation algorithm. Numerical results indicate that our proposed schemes greatly enhance the revenue of the VEC provider, and concurrently improve the utilization of cloud computing resources.},
	keywords = {Cloud, Contract theory, Mobile edge computing, Vehicular network},
	issn = {1572-8153},
	doi = {10.1007/s11036-018-1032-0},
	author = {Zhang, K. and Mao, Y. and Leng, S. and Maharjan, Sabita and Vinel, A. and Zhang, Yan}
}
@article {26434,
	title = {Cooperative Content Caching in 5G Networks with Mobile Edge Computing},
	journal = {IEEE Wireless Communications Magazine},
	volume = {25},
	number = {3},
	year = {2018},
	month = {06/2018},
	pages = {80-87},
	publisher = {IEEE},
	abstract = {Along with modern wireless networks being content-centric, the demand for rich multimedia services has been growing at a tremendous pace, which brings significant challenges to mobile networks in terms of the need for massive content delivery. Edge caching has emerged as a promising approach to alleviate the heavy burden on data transmission through caching and forwarding contents at the edge of networks. However, existing studies always treat storage and computing resources separately, and neglect the mobility characteristic of both the content caching nodes and end users. Driven by these issues, in this work, we propose a new cooperative edge caching architecture for 5G networks, where mobile edge computing resources are utilized for enhancing edge caching capability. In the architecture, we focus on mobility-aware hierarchical caching, where smart vehicles are taken as collaborative caching agents for sharing content cache tasks with base stations. To further utilize the caching resource of smart vehicles, we introduce a new vehicular caching cloud concept, and propose a vehicle-aided edge caching scheme, where the caching and computing resources at the wireless network edge are jointly scheduled. Numerical results indicate that the proposed scheme minimizes content access latency and improves caching resource utilization.},
	author = {Zhang, K. and Leng, S. and He, Y. and Maharjan, Sabita and Zhang, Yan}
}
@inproceedings {26343,
	title = {A Distributed Offloading Market for 5G Heterogeneous Network},
	journal = {IEEE Global Communications Conference},
	year = {2018},
	publisher = {IEEE},
	address = {Abu Dhabi,UEA},
	abstract = {Concerns have been raised regarding the economical viability for each operator to have a full regional 5G coverage. A possible solution is to have traffic offloaded to competitors. In this work we present a new scheme for optimal offloading in a stochastic environment. This is more in line with the conditions 5G base stations will face with changing link and traffic conditions. The problem is formulated as a Stackelberg game, and the players{\textquoteright} utility functions are derived though queuing models. Numerical results illustrate that our scheme provides a global optimal resource allocation up to a threshold. The threshold is a function of the traffic load and the number of offloading candidates. Beyond the threshold players still have incentives to participate, but the market equilibrium is not globally optimal.},
	author = {Kure, Endre and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@inproceedings {26342,
	title = {Energy Usage Forecasting for LTE: A Network-Wide Traffic Measurements Study},
	journal = {IEEE Global Communications Conference},
	year = {2018},
	publisher = {IEEE},
	address = {Abu Dhabi, UEA},
	abstract = {Energy usage in LTE base stations are driven by spectral efficiency and traffic. To predict the energy usage these parameters must be forecasted. In this work we analyse hourly measurements collected from more than 12000 base station cells spread across more than 3700 base stations over the course of one month. We show that the two parameters are very weakly correlated, and therefore we investigated them separately. Further, we evaluated the possible gains for advanced prediction methods using a large scale search for individually fitted time series (SARIMA models) for each base station. In total, we examined and evaluated approximately 31000 time series models from an identified group of 4 million potential models. We found that the spectral efficiency measurements can be represented fairly well with time series models, with only an average 6.5\% relative error. The time series models have to be individually adapted for each base station as the unsupervised clustering showed that each cluster{\textquoteright}s members have a wide variety of best fitted models. However, for traffic the time series models have relative high prediction errors, and we believe there is a potential for new methods to improve the forecasts.\&nbsp;\&nbsp;},
	author = {Kure, Endre and Engelstad, Paal and Maharjan, Sabita and Gjessing, Stein and Zhang, Xing and Zhang, Yan}
}
@article {26435,
	title = {Green Energy Scheduling for Demand Side Management in the Smart Grid},
	journal = {IEEE Transactions on Green Communications and Networking},
	volume = {2},
	number = {2},
	year = {2018},
	month = {06/2018},
	pages = {596-611},
	publisher = {IEEE},
	abstract = {Demand side management (DSM) is an essential property of smart grid systems. Along with increasing expectations related to power quality from customers, and as new types of loads emerge, such as electric vehicles, local (renewable) energy generation, and stationary and mobile energy storage, it is critical to develop new methods for DSM. In this paper, we first construct a more efficient and reliable communication infrastructure in smart grid based on cognitive radio technology, which is an essential component for enabling DSM. Then, we propose a distributed energy storage planning approach based on game algorithm in DSM, which helps users select the appropriate size of storage units for balancing the cost in the planning period and during its use. Since planning problems may lead to consumer discomfort, we propose a cost function consisting of the billing, generation costs, and discomfort costs to balance users{\textquoteright} preferences with the payment. Furthermore, a game theory-based distributed energy management scheme is developed in DSM without leaking user privacy, which is used as inner optimization in our proposed distributed energy storage planning approach. In this energy management scheme, Nash equilibrium is obtained with minimum information exchange using proximal decomposition algorithm. Simulation results show superior performance of our proposed DSM mechanism in reducing the peak-to-average ratio, total cost, user{\textquoteright}s daily payment, and energy consumption in smart grid communication networks.},
	author = {Wang, K. and Li, H. and Maharjan, Sabita and Zhang, Yan and Guo, S.}
}
@article {26442,
	title = {Joint Computation Offloading and User Association in Multi-task Mobile Edge Computing},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {67},
	year = {2018},
	month = {12/2018},
	pages = {12313-12325},
	publisher = {IEEE},
	abstract = {Computation intensive and delay-sensitive applications impose severe requirements on mobile devices of providing required computation capacity and ensuring latency. Mobile edge computing (MEC) is a promising technology that can alleviate computation limitation of mobile users and prolong their lifetime through computation offloading. However, computation offloading in an MEC environment faces severe issues due to dense deployment of MEC servers. Moreover, a mobile user has multiple mutually dependent tasks, which make offloading policy design even more challenging. To address the above-mentioned problems in this paper, we first propose a novel two-tier computation offloading framework in heterogeneous networks. Then, we formulate joint computation offloading and user association problem for multi-task mobile edge computing system to minimize overall energy consumption. To solve the optimization problem, we develop an efficient computation offloading algorithm by jointly optimizing user association and computation offloading where computation resource allocation and transmission power allocation are also considered. Numerical results illustrate fast convergence of the proposed algorithm, and demonstrate the superior performance of our proposed algorithm compared to state of the art solutions.},
	author = {Dai, Y. and Xu, D. and Maharjan, Sabita and Zhang, Yan}
}
@article {26441,
	title = {Joint Load Balancing and Offloading in Vehicular Edge Computing and Networks},
	journal = {IEEE Internet of Things Journal},
	year = {2018},
	month = {10/2018},
	publisher = {IEEE},
	abstract = {The emergence of computation intensive and delay sensitive on-vehicle applications makes it quite a challenge for vehicles to be able to provide the required level of computation capacity, and thus the performance. Vehicular Edge Computing (VEC) is a new computing paradigm with a great potential to enhance vehicular performance by offloading applications from the resource-constrained vehicles to lightweight and ubiquitous VEC servers. Nevertheless, offloading schemes where all vehicles offload their tasks to the same VEC server, can limit the performance gain due to overload. To address this problem, in this paper, we propose integrating load balancing with offloading, and study resource allocation for a multi-user multi-server VEC system. First, we formulate the joint load balancing and offloading problem as a mixed integer non-linear programming problem to maximize system utility. Particularly, we take IEEE 802.11p protocol into consideration for modeling the system utility. Then, we decouple the problem as two subproblems and develop a low-complexity algorithm to jointly make VEC server selection, and optimize offloading ratio and computation resource. Numerical results illustrate that the proposed algorithm exhibits fast convergence and demonstrates the superior performance of our joint optimal VEC server selection and offloading (JSCO) algorithm compared to the benchmark solutions.},
	author = {Dai, Y. and Xu, D. and Maharjan, Sabita and Zhang, Yan}
}
@inproceedings {26432,
	title = {Joint Offloading and Resource Allocation in Vehicular Edge Computing and Networks},
	journal = {IEEE Globecom 2018},
	year = {2018},
	publisher = {IEEE},
	abstract = {The emergence of computation intensive on-vehicle applications poses a significant challenge to provide the required computation capacity and maintain high performance. Vehicular Edge Computing (VEC) is a new computing paradigm with a high potential to improve vehicular services by offloading computation-intensive tasks to the VEC servers. Nevertheless, as the computation resource of each VEC server is limited, offloading may not be efficient if all vehicles select the same VEC server to offload their tasks. To address this problem, in this paper, we propose offloading with resource allocation. We incorporate the communication and computation to derive the task processing delay. We formulate the problem as a system utility maximization problem, and then develop a low-complexity algorithm to jointly optimize offloading decision and resource allocation. Numerical results demonstrate the superior performance of our Joint Optimization of Selection and Computation (JOSC) algorithm compared to state of the art solutions.},
	author = {Dai, Y. and Xu, D. and Maharjan, Sabita and Zhang, Yan}
}
@article {26437,
	title = {Mobile Edge Computing and Networking for Green and Low Latency Internet of Things},
	journal = {IEEE Communications Magazine},
	volume = {56},
	number = {5},
	year = {2018},
	month = {05/2018},
	pages = {39-45},
	publisher = {IEEE},
	abstract = {IoT, a heterogeneous interconnection of smart devices, is a great platform to develop novel mobile applications. Resource constrained smart devices, however, often become the bottlenecks to fully realize such developments, especially when it comes to intensive-computation-oriented and low-latency-demanding applications. MEC is a promising approach to address such challenges. In this article, we focus on MEC applications for IoT, and address energy efficiency as well as offloading performance of such applications in terms of end-user experience. In this regard, we present a mobility-aware hierarchical MEC framework for green and low-latency IoT. We deploy a game theoretic approach for computation offloading in order to optimize the utility of the service providers while also reducing the energy cost and the task execution time of the smart devices. Numerical results indicate that the proposed scheme does brings significant enhancement in both energy efficiency and latency performance of MEC applications for IoT.},
	author = {Zhang, K. and Leng, S. and He, Y. and Maharjan, Sabita and Zhang, Yan}
}
@article {26438,
	title = {Optimal Charging Schemes for Electric Vehicles in Smart Grid: A Contract Theoretic Approach},
	journal = {IEEE Transactions on Intelligent Transportaion Systems},
	volume = {19},
	year = {2018},
	month = {09/2018},
	pages = {3046-3058},
	publisher = {IEEE},
	abstract = {Due to their environment friendliness, electric vehicles (EVs) are anticipated to form a considerable fraction of vehicles for transportation in smart cities. It is essential to design an electricity charging scheme that takes the utilities of both the charging stations and the EVs into consideration. However, the self-interested nature of the EVs together with the information asymmetry between the energy demand and supply sides makes the design a significant challenge. In this paper, we propose a queuing network-based model to characterize the charging process of the multiple EVs in a renewable energy-aided charging station. Based on the model, we adopt a contract theoretic approach to design an optimal charging policy in an information asymmetry scenario. Furthermore, we propose the new contract-based charging rate assignment and admission control schemes that maximize the utility of the charging station under certain charging constraints. To derive the optimal contract, we present a two-step iterative algorithm and prove its convergence. We evaluate the proposed schemes based on the IEEE 69-bus distribution test system. Results indicate that the contract-based charging schemes can effectively benefit both the charging stations and the EVs and concurrently improve the load level of the smart grid.},
	author = {Zhang, K. and Mao, Y. and Leng, S. and He, Y. and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan and Tsang, D.}
}
@misc {26449,
	title = {When SDN, Edge Computing and Big Data Meet Intelligent Transport Systems},
	howpublished = {IEEE VTC Spring 2018, Porto, Portugal},
	year = {2018},
	type = {Tutorial},
	author = {Zhang, Yan and Maharjan, Sabita and Zhou, Z.}
}
@article {25827,
	title = {Capacity Analysis of NOMA With mmWave Massive MIMO Systems},
	journal = {IEEE Journal on Selected Areas in Communications},
	volume = {35},
	year = {2017},
	pages = {1606-1618},
	publisher = {IEEE},
	issn = {0733-8716},
	doi = {10.1109/JSAC.2017.2699059},
	author = {Zhang, Di and Zhou, Zhenyu and Xu, Chen and Zhang, Yan and Rodriguez, Jonathan and Sato, Takuro}
}
@article {25417,
	title = {Enabling Localized Peer-to-Peer Electricity Trading Among Plug-in Hybrid Electric Vehicles Using Consortium Blockchains},
	journal = {IEEE Transactions on Industrial Informatics},
	volume = {13},
	year = {2017},
	month = {05/2017},
	pages = {3154 - 3164},
	publisher = {IEEE},
	abstract = {We propose a localized Peer-to-Peer (P2P) electricity trading model for locally buying and selling electricity among Plug-in Hybrid Electric Vehicles (PHEVs) in smart grids. Unlike traditional schemes, that transport electricity over long distances and through complex electricity transportation meshes, our proposed model achieves demand response by providing incentives to discharging PHEVs to balance local electricity demand out of their own self-interests. However, since transaction security and privacy protection issues present serious challenges, we explore a promising consortium blockchain technology to improve transaction security without reliance on a trusted third party. A localized P2P Electricity Trading system with COnsortium blockchaiN (PETCON) method is proposed to illustrate detailed operations of localized P2P electricity trading. Moreover, the electricity pricing and the amount of traded electricity among PHEVs are solved by an iterative double auction mechanism to maximize social welfare in this electricity trading. Security analysis shows that our proposed PETCON improves transaction security and privacy protection. Numerical results based on a real map of Texas indicate that the double auction mechanism can achieve social welfare maximization while protecting privacy of the PHEVs.},
	keywords = {Consortium blockchain, decentralized energy trading, double auction, plug-in hybrid electric vehicles (PHEVs), security and privacy},
	issn = {1941-0050},
	doi = {10.1109/TII.2017.2709784},
	author = {Kang, Jiawen and Yu, Rong and Huang, Xumin and Maharjan, Sabita and Zhang, Yan and Hossain, Ekram}
}
@article {25828,
	title = {Information Caching Strategy for Cyber Social Computing Based Wireless Networks},
	journal = {IEEE Transactions on Emerging Topics in Computing},
	volume = {5},
	year = {2017},
	pages = {391-402},
	publisher = {IEEE},
	doi = {10.1109/TETC.2017.2699695},
	author = {Zhang, Xing and Li, Yongjing and Zhang, Yan and Zhang, Jiaxin and Li, Hailing and Wang, Shuo and Wang, Danyang}
}
@article {25578,
	title = {Mobile Edge Computing: A Survey},
	journal = {IEEE Internet of Things Journal},
	volume = {5},
	year = {2017},
	month = {02/2018},
	publisher = {ACM IEEE},
	abstract = {Mobile Edge Computing (MEC) is an emergent\&nbsp;architecture where cloud computing services are extended to the\&nbsp;edge of networks leveraging mobile base stations. As a promising\&nbsp;edge technology, it can be applied to mobile, wireless and wireline\&nbsp;scenarios, using software and hardware platforms, located at\&nbsp;the network edge in the vicinity of end-users. MEC provides\&nbsp;seamless integration of multiple application service providers\&nbsp;and vendors towards mobile subscribers, enterprises and other\&nbsp;vertical segments. It is an important component in the 5G\&nbsp;architecture which supports variety of innovative applications\&nbsp;and services where ultra low latency is required. This paper is\&nbsp;aimed to present a comprehensive survey of relevant research and\&nbsp;technological developments in the area of MEC. It provides the\&nbsp;definition of MEC, its advantages, architectures, and application\&nbsp;areas; where we in particular highlight related research and\&nbsp;future directions. Finally, security and privacy issues and related\&nbsp;existing solutions are also discussed.},
	keywords = {Fog Computing, IoT, Mobile cloud computing, Mobile edge computing},
	doi = {10.1109/JIOT.2017.2750180},
	author = {Abbas, Nasir and Zhang, Yan and Taherkordi, Amir and Skeie, Tor}
}
@article {25829,
	title = {Multi-Method Data Delivery for Green Sensor-Cloud},
	journal = {IEEE Communications Magazine},
	volume = {55},
	year = {2017},
	pages = {176-182},
	publisher = {IEEE},
	author = {Zhu, Chunsheng and Victor C. M. {Leung} and Wang, Kun and Laurence T. {Yang} and Zhang, Yan}
}
@article {25825,
	title = {A new lightweight RFID grouping authentication protocol for multiple tags in mobile environment},
	journal = {Multimedia Tools and Applications},
	volume = {76},
	year = {2017},
	pages = {22761{\textendash}22783},
	publisher = {Springer US},
	doi = {10.1007/s11042-017-4386-6},
	author = {Shen, Jian and Tan, Haowen and Zhang, Yan and Sun, Xingming and Xiang, Yang}
}
@inproceedings {26344,
	title = {Optimal battery size for a green base station in a smart grid with a renewable energy source},
	journal = {IEEE International Conference on Smart Grid Communications },
	year = {2017},
	publisher = {IEEE},
	address = {Dresden, Germany},
	abstract = {Green base stations, powered by renewable energy sources, have mainly been restricted to remote areas. In urban areas, recent technological advancements have strengthened the bidirectional power flow in microgrids (Smart Grids), giving the possibility of green LTE base stations acting as energy traders. To facilitate this trading, batteries are needed to deal with the inherent stochasticity of renewable energy sources. In this paper we provide a new technique for dimensioning batteries for a base station. We show how the solution depends on different boundary conditions set by the microgrid such as energy balancing cost, transaction fee and power price. The technique is based on a Markov decision process and considers uncertainty in traffic, renewable power production and power price in the microgrid. We also show how to quantify the energy balancing cost for the base station, supplementing current research on energy balancing in microgrids. The results show that for certain microgrid conditions, the value of modelling price uncertainty is insignificant. Also, the results show that it is never optimal to invest in more than the minimum required battery size given certain transaction fee and power price regimes.},
	doi = {10.1109/SmartGridComm.2017.8340658},
	url = {http://ieeexplore.ieee.org/document/8340658/http://xplorestaging.ieee.org/ielx7/8334844/8340652/08340658.pdf?arnumber=8340658},
	author = {Kure, Endre and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@inproceedings {25273,
	title = {Optimal Delay Constrained Offloading for Vehicular Edge Computing Networks},
	journal = {2017 IEEE International Conference on Communications (ICC)},
	year = {2017},
	publisher = {IEEE},
	abstract = {The increasing number of smart vehicles and their resource hungry applications pose new challenges in terms of computation and processing for providing reliable and efficient vehicular services. Mobile Edge Computing (MEC) is a new paradigm with potential to improve vehicular services through computation offloading in close proximity to mobile vehicles. However, in the road with dense traffic flow, the computation limitation of these MEC servers may endanger the quality of offloading service. To address the problem, we propose a hierarchical cloud-based Vehicular Edge Computing (VEC) offloading framework, where a backup computing server in the neighborhood is introduced to make up for the deficit computing resources of MEC servers. Based on this framework, we adopt a Stackelberg game theoretic approach to design an optimal multilevel offloading scheme, which maximizes the utilities of both the vehicles and the computing servers. Furthermore, to obtain the optimal offloading strategies, we present an iterative distributed algorithm and prove its convergence. Numerical results indicate that our proposed scheme greatly enhances the utility of the offloading service providers.},
	isbn = {978-1-4673-8999-0},
	issn = {1938-1883},
	doi = {10.1109/ICC.2017.7997360},
	author = {Zhang, Ke and Mao, Yuming and Leng, Supeng and Maharjan, Sabita and Zhang, Yan},
	editor = {IEEE, }
}
@article {25824,
	title = {SD-MAC: Spectrum Database-Driven MAC Protocol for Cognitive Machine-to-Machine Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {66},
	year = {2017},
	pages = {1456 - 1467},
	publisher = {IEEE},
	issn = {1939-9359},
	doi = {10.1109/TVT.2016.2555084},
	author = {Liu, Yi and Yu, Rong and Pan, Miao and Zhang, Yan and Xie, Shengli}
}
@article {25830,
	title = {Secure Multimedia Big Data in Trust-Assisted Sensor-Cloud for Smart City},
	journal = {IEEE Communications Magazine},
	volume = {55},
	year = {2017},
	pages = {24-30},
	publisher = {IEEE},
	doi = {10.1109/MCOM.2017.1700212},
	author = {Zhu, Chunsheng and Shu, Lei and Victor C. M. {Leung} and Guo, Song and Zhang, Yan and Laurence T. {Yang}}
}
@article {25639,
	title = {Selective Offloading in Mobile Edge Computing for Green Internet of Things},
	journal = {IEEE Network Magazine},
	volume = {32},
	year = {2017},
	pages = {54-60},
	publisher = {IEEE},
	abstract = {Mobile Edge Computing (MEC) provides the radio access networks with cloud computing capabilities to fulfill the requirements of the Internet of Things (IoT) services such as high reliability and low latency. Offloading services to edge servers can alleviate the storage and computing limitations and prolong the lifetimes of the IoT devices. However, offloading in MEC faces scalability problems due to the massive number of IoT devices. In this article, we present a new integration architecture of the cloud, MEC and IoT, and propose a lightweight request and admission framework to resolve the scalability problem. Without coordination among devices, the proposed framework can be operated at the IoT devices and computing servers separately, by encapsulating latency requirements in offloading requests. Then, a selective offloading scheme is designed to minimize the energy consumption of devices, where the signalling overhead can be further reduced by enabling the devices to be selfnominated or self-denied for offloading. Simulation results show that our proposed selective offloading scheme can satisfy the latency requirements of different services and reduce the energy consumption of the IoT devices.},
	keywords = {energy efficiency, Internet of things, Mobile edge computing, scalability, Selective offloading},
	doi = {10.1109/MNET.2018.1700101},
	author = {Lyu, X. and Tian, H. and Jiang, L. and Vinel, A. and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@article {25274,
	title = {Software Defined Energy Harvesting Networking for 5G Green Communications},
	journal = {IEEE Wireless Communications Magazine},
	volume = {24},
	year = {2017},
	pages = {38-45},
	publisher = {IEEE Wireless Communication Magazine},
	abstract = {Energy and spectrum resources play significant roles in fifth generation (5G) communication systems. In industrial applications of the 5G era, green communications are a great challenge for sustainable development of networks. Energy harvesting technology is a promising approach to prolong network lifetime. In energy harvesting networks, nodes may replenish energy from a mobile charger to overcome variations of renewable energy. In this article, energy-rich nodes are stimulated to upload surplus energy to the mobile charger, leading to a bidirectional energy flow. This creates a new paradigm that energy flows coexist with data flows, which gives rise to new problems on controlling the energy flows and the data flows. Software defined networking enables centralized control to optimize flow scheduling. We propose a Software Defined Energy Harvesting Network (SD-EHN) architecture for 5G green communications. In the SD-EHN, the data plane, the energy plane and the control plane are decoupled to support flexible energy scheduling and improve energy efficiency, thus to facilitate sustainability in energy harvesting networks. A scenario with a mobile charger acting as a mobile data collector is presented to introduce an energy trading model in SD-EHN. We use stochastic inventory theory to determine the optimal energy storage levels of the nodes. A Nash bargaining game is proposed to solve the benefit allocation problem for energy trading. Numerical results indicate that SD-EHN optimizes energy utilization and saves energy.},
	doi = {10.1109/MWC.2017.1600360},
	author = {Huang, Xumin and Yu, Rong and Kang, Jiawen and Gao, Yue and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@misc {25416,
	title = {Toturial on "Software Defined Wireless Networking"},
	howpublished = {Paris, France},
	year = {2017},
	publisher = {IEEE},
	type = {Tutorial},
	author = {Zhang, Yan and Maharjan, Sabita}
}
@article {25831,
	title = {Toward Big Data in Green City},
	journal = {IEEE Communications Magazine},
	volume = {55},
	year = {2017},
	pages = {14-18},
	publisher = {IEEE},
	doi = {10.1109/MCOM.2017.1700142},
	author = {Zhu, Chunsheng and Zhou, Huan and Victor C. M. {Leung} and Wang, Kun and Zhang, Yan and Laurence T. {Yang}}
}
@article {25826,
	title = {Wireless Big Data Computing in Smart Grid},
	journal = {IEEE Wireless Communications},
	volume = {24},
	year = {2017},
	pages = {58-64},
	publisher = {IEEE},
	issn = {1536-1284},
	doi = {10.1109/MWC.2017.1600256WC},
	author = {Wang, Kun and Wang, Yunqi and Hu, Xiaoxuan and Sun, Yanfei and Deng, Der-Jiunn and Vinel, Alexey and Zhang, Yan}
}
@article {23491,
	title = {Demand Response Management in the Smart Grid in a Large Population Regime},
	journal = {IEEE Transactions on Smart Grid},
	volume = {7},
	year = {2016},
	month = {01/2016},
	pages = {189-199},
	publisher = {IEEE},
	abstract = {In this paper we introduce a hierarchical system model that captures the decision making processes involved in a network of multiple providers and a large number of consumers in the smart grid, incorporating multiple processes from power generation to market activities and to power consumption. We establish a Stackelberg game between providers and end-users, where the providers behave as leaders maximizing their profit, and end-users act as followers maximizing their individual welfare. We obtain closed-form expressions for the Stackelberg equilibrium of the game and prove that a unique equilibrium solution exists. In the large population regime, we show that higher number of providers help improve profits for the providers. This is inline with the goal of facilitating multiple distributed power generation units, one of the main design considerations in the smart grid. We further prove that there exists a unique number of providers that maximize their profits, and develop an iterative and distributed algorithm to obtain it. Finally, we provide numerical examples to illustrate the solutions and to corroborate the results.},
	keywords = {Consumer welfare, Demand response management, large population, profit optimization, Stackelberg game},
	author = {Maharjan, Sabita and Zhu, Quanyan and Zhang, Yan and Gjessing, Stein and Basar, Tamer}
}
@article {24611,
	title = {Energy-efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks},
	journal = {IEEE Access},
	volume = {4},
	year = {2016},
	pages = {5896-5907},
	publisher = {IEEE},
	abstract = {Mobile Edge Computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading mechanisms for MEC in 5G heterogenous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogenous network, we then design an Energy-Efficient Computation Offloading (EECO) scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.},
	doi = {10.1109/ACCESS.2016.2597169},
	author = {Zhang, Ke and Mao, Yuming and Leng, Supeng and Zhao, Quanxin and Li, Longjiang and Peng, Xin and Pan, Li and Zhang, Guoyun and Maharjan, Sabita and Zhang, Yan}
}
@article {24548,
	title = {Incentive-Driven Energy Trading in the Smart Grid},
	journal = {IEEE Access},
	volume = {4},
	year = {2016},
	month = {03/2016},
	pages = {1243-1257},
	publisher = {IEEE},
	abstract = {The smart grid is widely considered as an efcient and intelligent power system. With the aid of communication technologies, the smart grid can enhance the efciency and reliability of the grid system through intelligent energy management. However, with the development of new energy sources, storage and transmission technologies together with the heterogeneous architecture of the grid network, several new features have been incorporated into the smart grid. These features make the energy trading more complex and pose a signicant challenge on designing efcient trading schemes. Based on this motivation, in this paper, we present a comprehensive review of several typical economic incentive approaches adopted in the energy-trading control mechanisms. We focus on the technologies that address the challenges specic to the new features of the smart grid. Furthermore, we investigate the energy trading in a new cloud-based vehicle-to-vehicle energy exchange scenario. We propose an optimal contract-based electricity trading scheme, which efciently increases the generated profit.},
	issn = {2169-3536},
	doi = {10.1109/ACCESS.2016.2543841},
	author = {Zhang, K. and Mao, Y. and Leng, Supeng and Maharjan, Sabita and Zhang, Yan and Vinel, A. and Jonsson, Magnus}
}
@inproceedings {24549,
	title = {On-demand Pseudonym Systems in Geo-distributed Mobile Cloud Computing},
	journal = {IEEE International Conference on Cyber Security and Cloud Computing (IEEE CS Cloud): Best Paper Award},
	year = {2016},
	note = {Won the Best Paper Award (IEEE CSCloud 2016)},
	publisher = {IEEE},
	abstract = {Geo-distributed mobile cloud computing (GMCC) integrates location information into mobile cloud computing, that has high potential for a large variety of applications. In a vehicular environment, a GMCC provides a large number of resources to vehicles that are geographically close to them. However, there are few studies that focus on security and privacy pseudonym management in GMCC system for vehicular environment. We design a three-layer on-demand pseudonym system to manage the pseudonyms. Moreover, we propose a secure pseudonym distribution scheme for secure communication among vehicles. As the number of demanded pseudonyms varies with traffic loads in different clouds, we use a newsvendor model to address the optimal on-demand pseudonym distribution problem. Numerical results indicate our proposed schemes not only improve utility of the clouds, but also maximize utilization of pseudonyms.},
	author = {Kang, J. and Yu, R. and Huang, X. and Maharjan, Sabita and Zhang, Yan}
}
@article {24768,
	title = {Optimal Incentive Design for Cloud-enabled Multimedia Crowdsourcing},
	journal = {IEEE Transactions on Multimedia},
	volume = {18},
	year = {2016},
	month = {08/2016},
	pages = {2470-2481},
	publisher = {IEEE},
	abstract = {Multimedia crowdsourcing possesses a huge potential to actualize many new applications that are expected to yield tremendous benefits in diverse fields including environment monitoring, emergency rescues during natural catastrophes, online education, sports and entertainment. Nonetheless, multimedia crowdsourcing unfolds new challenges such as big data acquisition and processing, more stringent QoS requirements, and heterogeneity of crowdsensors. Consequently, incentive mechanisms specifically tailored to multimedia crowdsourcing applications need to be developed to fully utilitze the potential of multimedia crowdsourcing. In this paper, we design an optimal incentive mechanism for the smartphone contributors to participate in a cloud-enabled multimedia crowdsourcing scheme. We establish a condition that determines whether the smartphones are eligible to participate, and provide a close form expression for the optimal duration of service from the contributors, for a given reward from the crowdsourcer. Consequently, we derive the conditions for existence of an optimal reward for the contributors from the crowdsourcer, and prove its uniqueness.We numerically illustrate the performance of our model considering logarithmic and linear cost functions for the cloud resources. The similarity of the results for different cost models corroborate the validity of our model and the results, whereas the difference in the magnitudes suggest that the strategy of the crowdsourcer as well as the strategies of the smartphone participants considerably depend on the cloud cost model.},
	doi = {10.1109/TMM.2016.2604080},
	author = {Maharjan, Sabita and Zhang, Yan and Gjessing, Stein}
}
@article {24766,
	title = {Quality of Protection in Cloud-Assisted Cognitive Machine-to-Machine Communications for Industrial Systems},
	journal = {ACM/Springer Mobile Networks and Applications},
	volume = {21},
	year = {2016},
	pages = {1032-1042},
	publisher = {ACM/Springer},
	abstract = {Cloud-assisted cognitive machine-to-machine communications (CM2M) is a new paradigm to improve the mobile services, which have drawn considerable attention in industry and academia. In this paper, we consider the quality of protection (QoP) of information transmission in cloud-assisted CM2M communications. In such an environment, the secondary M2M system intends to share the primary spectrum on the condition that the secondary transmitter (ST) has to relay the primary message. However, the ST is a low-energy device which adopts the energy harvesting technique to power itself. In particular, we focus on secure information transmission for the primary system when the secondary users (SUs) are the potential eavesdroppers. We aim to jointly design power splitting and secure beamforming to maximize the secondary M2M system data rate subject to the secrecy requirement of the primary system and the ST power constraint. To solve this non-convex problem, we propose a computationally efficient two-stage optimization approach. Simulation results demonstrate that our proposed scheme achieves a significant transmission rate of the secondary M2M system while provides a high secrecy rate for the primary system compared to the scheme without energy harvesting.},
	author = {Jiang, L. and Tian, H. and Shen, J. and Maharjan, Sabita and Zhang, Yan}
}
@article {24767,
	title = {Social Computing for Mobile Big Data},
	journal = {IEEE Computer},
	volume = {49},
	year = {2016},
	month = {09/2016},
	publisher = {IEEE},
	abstract = {Mobile big data contains vast statistical features in various dimensions, including spatial, temporal, and the underlying social domain. Understanding and exploiting the features of mobile data from a social network perspective will be extremely beneficial to wireless networks, from planning, operation, and maintenance to optimization and marketing.},
	issn = {0018-9162 },
	doi = {10.1109/MC.2016.267},
	url = {http://ieeexplore.ieee.org/document/7562344/},
	author = {Zhang, X. and Yi, Z. and Yan, Z. and Min, G. and Wang, W. and Elmokashfi, Ahmed and Maharjan, Sabita and Zhang, Yan}
}
@article {24546,
	title = {Social-aware Energy Harvesting Device to Device Communications in 5G Networks},
	journal = {IEEE Wireless Communication Magazine},
	volume = {23},
	year = {2016},
	pages = {20-27},
	publisher = {IEEE},
	abstract = {With ever-increasing demands for local area services in the fifth generation (5G) cellular networks, solutions are necessary to deliver local area data in both a spectrum- and an energy-efficient manner. In this paper we propose a new cellular communication architecture which integrates energy harvesting technologies and social networking characteristics into device-to-device (D2D) communications for local data dissemination. The proposed architecture includes three domains: the physical domain, the energy domain and the social domain. Specifically, in the physical domain, D2D communications enable two nearby users to communicate with each other directly. In the energy domain, devices harvest energy from renewable energy sources. In the social domain, D2D users form social networks exhibiting stable social structures and relations. Then we mainly focus on the efficient local data dissemination issues in the proposed architecture and propose two social-aware energy harvesting D2D communication schemes (a device relaying and a device multicast). Illustrative results demonstrate significant spectrum and energy efficiency enhancement for local data dissemination in 5G cellular networks.},
	author = {Jiang, L. and Tian, H. and Xing, Z. and Wang, K. and Zhang, K. and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@article {24545,
	title = {Software Defined Networking with Pseudonym Systems for Secure Vehicular Clouds},
	journal = {IEEE Access},
	volume = {4},
	year = {2016},
	month = {04/2016},
	pages = {3522-3534},
	publisher = {IEEE},
	abstract = {The vehicular cloud is a promising new paradigm, where vehicular networking and mobile cloud computing are elaborately integrated to enhance the quality of vehicular information services. Pseudonym is a resource for vehicles to protect their location privacy, which should be efciently utilized to secure vehicular clouds. However, only a few existing architectures of pseudonym systems take exibility and efciency into consideration, thus leading to potential threats to location privacy. In this paper, we exploit software-dened networking technology to signicantly extend the exibility and programmability for pseudonym management in vehicular clouds. We propose a software-dened pseudonym system, where the distributed pseudonym pools are promptly scheduled and elastically managed in a hierarchical manner. In order to decrease the system overhead due to the cost of inter-pool communications, we leverage the two-sided matching theory to formulate and solve the pseudonym resource scheduling. We conducted extensive simulations based on the real map of San Francisco. Numerical results indicate that the proposed software-dened pseudonym system signicantly improves the pseudonym resource utilization, and meanwhile, effectively enhances the vehicles\&$\#$39; location privacy by raising their entropy.},
	issn = {2169-3536 },
	doi = {10.1109/ACCESS.2016.2560902},
	author = {Huang, X. and Yu, R. and Kang, J. and Wang, N. and Maharjan, Sabita and Zhang, Yan}
}
@misc {25271,
	title = {Tutorial on Software Defined Wireless Networking},
	howpublished = {Valencia, Spain},
	year = {2016},
	publisher = {IEEE},
	type = {Tutorial},
	address = {PIMRC 2016},
	author = {Zhang, Yan and Maharjan, Sabita}
}
@inproceedings {24525,
	title = {Adaptive Rate Control in Smart Grid Heterogenous Communications Networks},
	journal = {IEEE CIT 2015 (Best Paper Award)},
	year = {2015},
	author = {Zhong, W. and Yu, R. and Zhang, Yan and Gao, Y. and Gjessing, Stein}
}
@article {23727,
	title = {Balancing Power Demand through EV Mobility in Vehicle-to-Grid Mobile Energy Networks},
	journal = { IEEE Transactions on Industrial Informatics},
	volume = {12},
	year = {2015},
	month = {02/2016},
	pages = {79-90},
	publisher = {IEEE},
	author = {Yu, Rong and Zhong, Weifeng and Xie, Shengli and Yuen, Chau and Gjessing, Stein and Zhang, Yan}
}
@article {23516,
	title = {A Collaborative Intrusion Detection Mechanism against False Data Injection in Advanced Metering Infrastructure},
	journal = {IEEE Transactions on Smart Grid},
	volume = {6},
	year = {2015},
	month = {09/2015},
	pages = {2435-2443},
	publisher = {IEEE},
	author = {Liu, X. and Zhu, P. and Zhang, Yan and Chen, K.}
}
@article {23512,
	title = {Connectivity of Cognitive Device-to-Device Communications Underlying Cellular Networks},
	journal = {IEEE Journal on Selected Areas in Communications (IEEE JSAC)},
	volume = {33},
	year = {2015},
	month = {05/2015},
	publisher = {IEEE},
	author = {Khoshkholgh, M. and Zhang, Yan and Chen, K. and Kang G. {Shin} and Gjessing, Stein}
}
@article {23726,
	title = {Cooperative Resource Management in Cloud-enabled Vehicular Networks},
	journal = {IEEE Transactions on Industrial Electronics},
	volume = {62},
	year = {2015},
	month = {12/2015},
	pages = {7938-7951},
	publisher = {IEEE},
	author = {Yu, Rong and Huang, X. and Kang, Jiawen and Ding, Jiefei and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@article {23618,
	title = {Decentralized and Optimal Resource Cooperation in Geo-distributed Mobile Cloud Computing},
	journal = {IEEE Transactions on Emerging Topics in Computing},
	year = {2015},
	publisher = {IEEE Transactions on Emerging Topics in Computing},
	abstract = {Mobile cloud computing is a key enabling technology in the era of Internet-of-Things. Geo-distributed mobile cloud computing (GMCC) is a new scenario that adds geography consideration in mobile cloud computing. In GMCC, users are able to access cloud resource that are geographically close to their mobile devices. This is expected to reduce communications delay and service providers\&rsquo; cost compared to the traditional centralized approach. In this paper, we focus on resource sharing through cooperation among service providers in geo-distributed mobile cloud computing. Then, we propose two different strategies for efficient resource cooperation in geographically distributed data centers. Further, we present a coalition game theoretical approach to deal with the competition and cooperation among service providers. Utility functions have been specifically considered to incorporate the cost related to virtual machine migration and resource utilization. Illustrative results indicate that our proposed schemes are able to efficiently utilize limited resource with Quality-of-Service (QoS) consideration.},
	keywords = {cooperation, game theory, Mobile cloud computing, resource management},
	author = {Yu, R. and Ding, J. and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan and Tsang, Danny}
}
@inproceedings {23831,
	title = {Dynamic Resource Pricing and Scalable Cooperation for Mobile Cloud Computing},
	journal = {The 15th IEEE International Conference on Scalable Computing and Communications (Best paper award)},
	year = {2015},
	month = {08/2015},
	publisher = {IEEE},
	abstract = {Mobile cloud computing is a new paradigm to improve the quality of mobile services, which has drawn considerable attentions in both industrial and academic fields. In this paper, we consider the resource management and sharing problems for radio and computing resources to support mobile applications in mobile cloud computing. In such an environment, service providers can cooperate to form coalition to share their idle resources with each other. We propose a coalition game model based on two-sided matching theory. The coalition game model efficiently reflects the scalable cooperation among the service providers for sharing their idle resources. As a result, the resources can be better utilized and the quality of service for users can be improved. The simulation results indicate that our scheme can optimize the resource utilization and significantlyimprove the quality of service of the users.},
	author = {Huang, Xumin and Yu, Rong and Kang, Jiawen and Ding, Jiefei and Maharjan, Sabita and Gjessing, Stein and Zhang, Yan}
}
@inproceedings {23722,
	title = {Evaluating Defence Schemes Against Jamming in Vehicle Platoon Networks},
	journal = {Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International},
	year = {2015},
	keywords = {Global Positioning System, Interference, Jamming, Sensors, Vehicles, Wireless communication},
	doi = {10.1109/ITSC.2015.348},
	author = {Patounas, Georgios},
	editor = {Zhang, Yan and Gjessing, Stein}
}
@inproceedings {23488,
	title = {Group Bidding for Guaranteed Quality of Energy in V2G Smart Grid Networks},
	journal = {IEEE International Conference on Communications},
	year = {2015},
	month = {06/2015},
	publisher = {IEEE},
	address = {London, UK},
	abstract = {With the aid of advanced Information and Communication Technologies (ICT), Vehicle-to-Grid (V2G) networks will play an important role in supporting and enhancing the distributed electricity supply in the next generation power grid{\textendash}smart grid. In order to ensure stability of the power grid and satisfy the Quality of Energy (QoE) requirements of Electric Vehicles (EVs), this paper proposes a two-level group bidding mechanism for the electric energy trade between the grid and EVs. Communication networks are used to support the exchange of relevant information between the grid and EVs. EVs act as mobile energy storage and compete to be one of the members in the electricity feedback group organized by aggregators. We aim at minimizing the cost of given electricity demand of the grid and maximizing the profit of those auction winner EVs. A quantity based feedback electricity unit pricing scheme is proposed to incentivize the participation of EVs in V2G networks. Moreover, Vickrey-Clarke-Groves (VCG) auction-based algorithms are designed to implement our proposed mechanisms. Simulation results indicate that our mechanism is able to reduce the cost of the grid while offer EVs significant incentives to participate inthe V2G power market.},
	keywords = {auction, groupselling, truthful bidding strategy, Vehicle-to-Grid (V2G) networks},
	author = {Zeng, Ming and Maharjan, Sabita and Zhang, Yan and Gjessing, Stein}
}
@article {23513,
	title = {Integrated Energy and Spectrum Harvesting for 5G Wireless Communications},
	journal = {IEEE Network},
	volume = {29},
	year = {2015},
	month = {05/2015},
	pages = {75-81},
	publisher = {IEEE},
	author = {Liu, Y. and Zhang, Yan and Yu, Rong and Xie, Shengli}
}
@misc {23729,
	title = {Intelligent Demand Response towards Green and Reliable Smart Energy Networks},
	howpublished = {the 14th the International Conference on Ad Hoc Networks and Wireless (ADHOC-NOW), June/July 2015, Greece},
	year = {2015},
	type = {Invited talk},
	author = {Zhang, Yan}
}
@article {23724,
	title = {Investigation of Transmission Schemes for Millimeter-Wave Massive MU-MIMO Systems},
	journal = {IEEE Systems Journal},
	volume = {PP},
	year = {2015},
	month = {12/2015},
	pages = {1-12},
	publisher = {IEEE},
	author = {Han, Y. and Jin, S. and Li, X. and Zhang, H. and Yu, R. and Zhang, Yan}
}
@article {23510,
	title = {Joint Relay Scheduling, Channel Access, and Power Allocation for Green Cognitive Radio Communications},
	journal = { IEEE Journal on Selected Areas in Communications (IEEE JSAC)},
	volume = {33},
	year = {2015},
	month = {05/2015},
	pages = {922 - 932},
	publisher = {IEEE},
	author = {Luo, C. and Min, G. and Yu, F. and Zhang, Yan and Yang, L. and Leung, V.}
}
@article {23517,
	title = {Macro-assisted Data-only Carrier for 5G Green Cellular Systems},
	journal = {IEEE Communications Magazine},
	volume = {53},
	year = {2015},
	month = {05/2015},
	pages = {223-231},
	publisher = {IEEE},
	author = {Zhang, X. and Zhang, Jin and Zhang, Yan and Wang, W.}
}
@article {23514,
	title = {MixGroup: Accumulative Pseudonym Exchanging for Location Privacy Enhancement in Vehicular Social Networks},
	journal = {IEEE Transactions on Dependable and Secure Computing},
	volume = {13},
	year = {2015},
	month = {01/2016},
	pages = {93-105},
	publisher = {IEEE},
	author = {Yu, Rong and Kang, Jiawen and Huang, X. and Xie, Shengli and Zhang, Yan and Gjessing, Stein}
}
@article {23728,
	title = {Mobile Big Data Fault-Tolerant Processing for eHealth Networks},
	journal = {IEEE Network Magazine},
	volume = {30},
	year = {2015},
	month = {01/2016},
	pages = {36-42},
	publisher = {IEEE},
	author = {Wang, K. and Shao, Y. and Shu, L. and Zhu, C. and Zhang, Yan}
}
@inproceedings {24523,
	title = {An Optimal Replenishment Strategy in Energy Harvesting Wireless Networks with A Mobile Charger},
	journal = {QSHINE 2015 (Best Paper Award)},
	year = {2015},
	author = {Yu, R. and Huang, X. and Kang, J. and Yuen, C. and Vinel, A. and Jonsson, Magnus and Gjessing, Stein and Zhang, Yan}
}
@article {23511,
	title = {Performance Analysis of Cognitive Relay Networks Over Nakagami-m Fading Channels},
	journal = {IEEE Journal on Selected Areas in Communications (IEEE JSAC)},
	volume = {33},
	year = {2015},
	month = {05/2015},
	pages = {865-877},
	publisher = {IEEE},
	author = {Zhang, X. and Zhang, Yan and Xiang, Jie and Wang, W.}
}
@article {23519,
	title = {Performance Analysis of Cognitive Relay Networks Over Nakagami-m Fading Channels},
	journal = {IEEE Journal on Selected Areas in Communications (IEEE JSAC)},
	volume = {33},
	year = {2015},
	month = {05/2015},
	pages = {865-877},
	publisher = {IEEE},
	author = {Zhang, X. and Zhang, Yan and Yan, Z. and Xiang, Jie and Wang, W.}
}
@article {23721,
	title = {Performance Analysis of Connectivity Probability and Connectivity-aware MAC Protocol Design for Platoon-based VANETs},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {64},
	year = {2015},
	month = {12/2015},
	pages = {5596-5609},
	publisher = {IEEE},
	author = {Shao, Caixing and Zhang, Yan and Vinel, Alexy and Jonsson, Magnus}
}
@inproceedings {24522,
	title = {Price-based Energy Control for V2G Networks in the Industrial Smart Grid},
	journal = {INISCOM 2015 (Best Paper Award)},
	year = {2015},
	author = {Yu, R. and Ding, J. and Zhong, W. and Zhang, Yan and Gjessing, Stein and Vinel, A. and Jonsson, Magnus}
}
@inproceedings {23693,
	title = {Providing Microgrid Resilience during Emergencies using Distributed Energy Resources},
	journal = {Globecom 2015},
	year = {2015},
	month = {12/2015},
	publisher = {IEEE},
	abstract = {Several incidents reported in the past have shown the inability of the existing power grid to provide reliable services during system failures. Moreover, the communication and control network in the smart grid inherently creates opportunities for the adversaries to launch cyber attacks to the system. Natural disasters may further exacerbate the challenge. Designing resilient (if not robust) solutions for the smart grid therefore, was, and remains a high priority. To this end, we present three solutions towards resilience of a microgrid during emergencies. First, we propose the use of electric vehicles (EVs) as temporary power supplies to support critical infrastructure during emergencies. Second, we recommend to use a combination of distributed renewable energy sources, EVs and a community-level storage unit to further enhance the resilience of the microgrid, by utilizing the locally available renewable energy options, exploiting the electric vehicles moderately, and by investing reasonably on the storage unit. Third, we introduce the software defined networking paradigm as a highly relevant platform for both power virtualization and network function virtualization, to support, coordinate and control the dynamic operation of the virtual power plants for reliable power supply and resilient operations of the microgrid in the disaster mode. Finally, we discuss the feasibility of each of these solutions for implementing them in practice.},
	keywords = {Community-level storage, distributed energy generation, electric vehicles, emergency, microgrid, Resilience, software defined networking.},
	author = {Maharjan, Sabita and Zhang, Yan and Gjessing, Stein and Ulleberg, {\O}yestein and Eliassen, Frank}
}
@article {23515,
	title = {QoS Differential Scheduling in Cognitive Radio Based Smart Grid Networks: An Adaptive Dynamic Programming Approach},
	journal = {IEEE Transactions on Neural Networks and Learning Systems},
	volume = {27},
	year = {2015},
	month = {02/2016},
	pages = {435-443},
	publisher = {IEEE},
	author = {Yu, Rong and Zhong, W. and Xie, Shengli and Zhang, Yan}
}
@article {23518,
	title = {Queuing-Based Energy Consumption Management for Heterogeneous Residential Demands in Smart Grid},
	journal = {IEEE Transaction on Smart Grid},
	year = {2015},
	publisher = {IEEE},
	author = {Liu, Y. and Yuen, C. and Yu, Rong and Zhang, Yan and Xie, Shengli}
}
@article {23723,
	title = {Service Providers Competition and Cooperation in Cloud-based Software Defined Wireless Networks},
	journal = {IEEE Communications Magazine},
	volume = {53},
	year = {2015},
	month = {11/2015},
	pages = {134-140},
	publisher = {IEEE},
	author = {Ding, Jiefei and Yu, Rong and Zhang, Yan and Gjessing, Stein and Tsang, Danny}
}
@article {23495,
	title = {Toward Secure Energy Harvesting Cooperative Networks},
	journal = {IEEE Communications Magazine},
	volume = {53},
	year = {2015},
	month = {08/2015},
	pages = {114-121},
	publisher = {IEEE},
	abstract = {Energy harvesting cooperative networks is an emerging technology that has very high potential for a large variety of applications. However, the energy transfer capability may lead to unprecedented security challenges. In this paper, we will study energy security issues and the solutions in energy harvesting networks. We first identify typical energy related attacks and then propose defense solutions against these attacks. We also carry out security analysis and performance analysis to evaluate our proposed solutions. Simulation results have shownthat the proposed defense solutions are effective and efficient.},
	keywords = {cooperative relay, energy attack, Energy harvesting cooperative networks, security and defense},
	author = {Kang, Jiawen and Yu, Rong and Maharjan, Sabita and Zhang, Yan and Huang, Xumin and Xie, Shengli and Bogucka, Hanna and Gjessing, Stein}
}
@inproceedings {24520,
	title = {Analysis of Connectivity Probability in Platoon-based Vehicular Ad Hoc Networks},
	journal = {IWCMC 2014 (Best Paper Award)},
	year = {2014},
	author = {Shao, C. and Leng, Supeng and Zhang, Yan and Vinel, A. and Jonsson, Magnus}
}
@inproceedings {23620,
	title = {Component-based modelling for sustainable and scalable smart meter networks},
	journal = {IEEE 15th International Symposium on "A World of Wireless, Mobile and Multimedia Networks"},
	year = {2014},
	month = {06/2014},
	pages = {1-6},
	publisher = {IEEE Computer Society},
	address = {Sydney},
	abstract = {It is expected that the Internet of Things (IoT) provides the foundational infrastructure for smart cities, and making ICT an enabling technology to meet major challenges associated with climate change, energy efficiency, mobility and future services. On the other hand a smart city with these requirements is usually evolving through incremental automation and integration of new components, that are digital or physical components or smart devices. To handle the growing scale and complexity of a system, an adaptive modelling method is needed for dynamic analysis and verification and/or validation, and integration. In this paper, we consider the case study of a Demand Response (DR) Programme that is to be realized by the deployment of a network of smart meters. Through this case study, we propose a component-based modelling approach and demonstrate how it deals with the growing complex architecture.},
	isbn = { 978-1-4799-4786-7},
	doi = {10.1109/WoWMoM.2014.6918927},
	url = {http://www.computer.org/csdl/proceedings/wowmom/2014/4786/00/06918927-abs.html},
	author = {Palomar, Esther and Liu, Zhiming and Jonathan P. {Bowen} and Zhang, Yan and Maharjan, Sabita}
}
@misc {Simula.simula.3120,
	title = {Cyber-Physical Smart Grid Systems},
	howpublished = {The 8th International Conference Interdisciplinarity in Engineering (INTER-ENG 2014)},
	year = {2014},
	month = {10/2014},
	author = {Zhang, Yan}
}
@article {Simula.simula.3112,
	title = {Demand Response Management With Multiple Utility Companies: a Two-Level Game Approach},
	journal = {IEEE Transactions on Smart Grid},
	volume = {5},
	number = {2},
	year = {2014},
	author = {Chai, B. and Chen, J. and Yang, Z. and Zhang, Yan}
}
@article {Simula.simula.3104,
	title = {Distributed Resource Allocation in Cloud-Based Wireless Multimedia Social Networks},
	journal = {IEEE Network},
	volume = {28},
	number = {4},
	year = {2014},
	pages = {74-80},
	author = {Nan, G. and Mao, Z. and Li, M. and Zhang, Yan and Gjessing, Stein and Wang, H. and Guizani, M.}
}
@article {24500,
	title = {An efficient hybrid spectrum access algorithm in OFDM-based wideband cognitive radio networks},
	journal = {Neurocomputing},
	volume = {125},
	year = {2014},
	pages = {33-40},
	publisher = {Elsevier},
	author = {Yang, Chao and Fu, Yuli and Zhang, Yan and Yu, Rong and Liu, Yi}
}
@article {Simula.simula.3118,
	title = {Energy-Efficient Multimedia Transmissions Through Base Station Cooperation Over Heterogeneous Cellular Networks Exploiting User Behavior},
	journal = {IEEE Wireless Communications},
	volume = {21},
	number = {4},
	year = {2014},
	author = {Zhang, X. and Yu, Rong and Zhang, Yan and Gao, Y. and Im, M. and Cuthbert, L. and Wang, W.}
}
@article {Simula.simula.3106,
	title = {An Enhanced Public Key Infrastructure to Secure Smart Grid Wireless Communication Networks},
	journal = {IEEE Network},
	volume = {28},
	number = {1},
	year = {2014},
	pages = {10-16},
	author = {He, D. and Chan, S. and Zhang, Yan and Guizani, M.}
}
@article {Simula.simula.3114,
	title = {Enhancing Spectral-Energy Efficiency for LTE-Advanced Heterogeneous Networks: a Users Social Pattern Perspective},
	journal = {IEEE Wireless Communications},
	volume = {21},
	number = {2},
	year = {2014},
	author = {Zhang, X. and Zhang, Yan and Yu, Rong and Wang, W. and Guizani, M.}
}
@article {Simula.simula.3152,
	title = {How Effective Are the Prevailing Attack-Defense Models for Cyber Security Anyway},
	journal = {IEEE Intelligent Systems},
	volume = {29},
	number = {5},
	year = {2014},
	author = {He, D. and Chan, S. and Zhang, Yan}
}
@inproceedings {24521,
	title = {Hybrid Spectrum Sharing in Cognitive Two-Way Relay Networks},
	journal = {WPMC 2014 (Best Paper Award)},
	year = {2014},
	author = {Zhang, X. and Zhang, Yan and Zhang, Z. and Xiang, Jie and Wang, W.}
}
@article {Simula.simula.3110,
	title = {Lightweight and Confidential Data Discovery and Dissemination for Wireless Body Area Networks},
	journal = {IEEE Journal of Biomedical and Health Informatics},
	volume = {18},
	number = {2},
	year = {2014},
	author = {He, D. and Chan, S. and Zhang, Yan and Yang, H.}
}
@article {24496,
	title = {A multi-priority supported medium access control in Vehicular Ad Hoc Networks},
	journal = {Computer Communications},
	volume = {39},
	year = {2014},
	pages = {367-374},
	publisher = {Elsevier},
	author = {Shao, Caixing and Leng, Supeng and Zhang, Yan and Fu, Huirong}
}
@article {Simula.simula.2412,
	title = {Role-Dependent Privacy Preservation for Secure V2G Networks in the Smart Grid},
	journal = {IEEE Transactions on Information Forensics \& Security},
	volume = {9},
	number = {2},
	year = {2014},
	pages = {208-220},
	author = {Liu, H. and Ning, H. and Zhang, Yan and Xiong, Q. and Yang, L.}
}
@article {Simula.simula.3116,
	title = {A Semiblind Two-Way Training Method for Discriminatory Channel Estimation in MIMO Systems},
	journal = {IEEE Transactions on Communications},
	volume = {62},
	number = {7},
	year = {2014},
	author = {Yang, J. and Xie, Shengli and Zhou, Xing and Yu, Rong and Zhang, Yan}
}
@article {Simula.simula.3108,
	title = {Spectrum and Energy Efficiency Evaluation of Two-Tier Femtocell Networks With Partially Open Channels},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {63},
	number = {3},
	year = {2014},
	author = {Ge, X. and Han, T. and Zhang, Yan and Mao, G. and Wang, C. and Zhang, Jin}
}
@article {Simula.simula.3102,
	title = {Stackelberg Game for Bandwidth Allocation in Cloud-Based Wireless Live-Streaming Social Networks},
	journal = {IEEE Systems Journal},
	volume = {8},
	number = {1},
	year = {2014},
	pages = {256-267},
	author = {Nan, G. and Mao, Z. and Yu, M. and Li, M. and Wang, H. and Zhang, Yan}
}
@article {23493,
	title = {User-Centric Demand Response Management in the Smart Grid With Multiple Providers},
	journal = {IEEE Transactions on Emerging Topics in Computing},
	year = {2014},
	note = {Accepted for publication in IEEE Transactions on Emerging Topics in Computing. Published Online: July 8, 2014},
	month = {07/2015},
	publisher = {IEEE},
	abstract = {The smart grid is the next generation power grid with bidirectional communications between the electricity users and the providers. Demand response management is vital in the smart grid to reduce power generation costs as well as to lower the users{\textquoteright} electricity bills. In this paper, we introduce multiple fossil-fuel and multiple renewable energy sources-based utility companies on the supply side, and propose an end-user oriented utility company selection scheme to minimize user costs. We formulate the problem as a game, incorporating the uncertainty associated with the power supply of the renewable sources, and prove that there exists a Nash equilibrium for the game. To further reduce users{\textquoteright} costs, we develop a joint scheme by integrating shiftable load scheduling with utility company selection. We model the joint scheme also as a game, and prove the existence of a Nash equilibrium for the game. For both schemes, we propose distributedalgorithms for the users to nd the equilibrium of the game using only local information. We evaluate our schemes and compare their performances to two other approaches. The results show that our joint utility company selection and shiftable load scheduling scheme incurs the least cost to the users.},
	keywords = {Demand response management, discrete time Markov chain, game theory, Nash equilibrium, renewable energy sources, smart grid, user cost.},
	author = {Maharjan, Sabita and Zhang, Yan and Gjessing, Stein and Tsang, Danny}
}
@article {24499,
	title = {Adaptive GTS allocation in IEEE 802.15.4 for real-time wireless sensor networks},
	journal = {Jurnal of Systems Architecture},
	volume = {59},
	year = {2013},
	pages = {1231-1242},
	publisher = {Elsevier},
	author = {Xia, Feng and Hao, Ruonan and Li, Jie and Xiong, Naixue and Laurence T. {Yang} and Zhang, Yan}
}
@article {Simula.simula.1764,
	title = {Battery Status-Aware Authentication Scheme for V2G Networks in Smart Grid},
	journal = {IEEE Transactions on Smart Grid},
	volume = {4},
	number = {1},
	year = {2013},
	pages = {99-110},
	author = {Liu, H. and Ning, H. and Zhang, Yan and Guizani, M.}
}
@article {Simula.simula.1566,
	title = {Dependable Demand Response Management in the Smart Grid: a Stackelberg Game Approach},
	journal = {IEEE Transactions on Smart Grid},
	volume = {4},
	number = {1},
	year = {2013},
	pages = {120-132},
	abstract = {Demand Response Management (DRM) is a key component in the smart grid to effectively reduce power generation costs and user bills. However, it has been an open issue to address the DRM problem in a network of multiple utility companies and consumers where every entity is concerned about maximizing its own benefit. In this paper, we propose a Stackelberg game between utility companies and end-users to maximize the revenue of each utility company and the payoff of each user. We derive analytical results for the Stackelberg equilibrium of the game and prove that a unique solution exists. We develop a distributed algorithm which converges to the equilibrium with only local information available for both utility companies and end-users. Though DRM helps to facilitate the reliability of power supply, the smart grid can be succeptible to privacy and security issues because of communication links between the utility companies and the consumers. We study the impact of an attacker who can manipulate the price information from the utility companies. We also propose a scheme based on the concept of shared reserve power to improve the grid reliability and ensure its dependability.},
	author = {Maharjan, Sabita and Zhu, Quanyan and Zhang, Yan and Gjessing, Stein and Basar, Tamer}
}
@article {Simula.simula.2418,
	title = {An Efficient MAC Protocol With Selective Grouping and Cooperative Sensing in Cognitive Radio Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {62},
	number = {8},
	year = {2013},
	pages = {3928-3941},
	author = {Liu, Y. and Xie, Shengli and Zhang, Yan and Yu, Rong and Yuen, C.}
}
@article {24508,
	title = {Enabling low bit-rate and reliable video surveillance over practical wireless sensor network},
	journal = {The Journal of Supercomputing},
	volume = {65},
	year = {2013},
	pages = {287-300},
	publisher = {Springer},
	author = {Chen, Min and Gonz{\'a}lez, Sergio and Cao, Huasong and Zhang, Yan and Son T. {Vuong}}
}
@misc {Simula.simula.2420,
	title = {Green and Secure Smart Grid},
	howpublished = {MACOM 2013 conference keynote},
	year = {2013},
	abstract = {Smart grid will integrate the state-of-the-art ICT technologies to significantly improve the efficiency, sustainability, security, and stability of the traditional power grid. In this talk, we will present our recent studies to address two major challenges in the smart grid: greenness and cyber security. In particular, the talk mainly includes three parts. In the first part, we introduce the smart grid scenarios, key concepts, and communications architectures. In the second part, we will present the greenness aspect based on a game-theoretical demand response management framework. In the third part, we will present cyber security aspects and a context-aware authentication scheme in Vehicle-to-Grid (V2G) communications systems when there is wide penetration of Electronic Vehicles.},
	author = {Zhang, Yan}
}
@misc {Simula.simula.2426,
	title = {Green Smart Grid},
	howpublished = {UGAF Green IT School / University of Oslo},
	year = {2013},
	abstract = {UGAF Green IT School / University of Oslo, 7 - 11 October 2013},
	author = {Zhang, Yan}
}
@article {Simula.simula.1756,
	title = {Grouping-Proofs Based Authentication Protocol for Distributed RFID Systems},
	journal = {IEEE Transactions on Parallel and Distributed Systems},
	volume = {24},
	number = {7},
	year = {2013},
	pages = {1321-1330},
	author = {Liu, H. and Ning, H. and Zhang, Yan and He, D. and Xiong, Q. and Yang, L.}
}
@misc {Simula.simula.2424,
	title = {Mobile Cloud Computing},
	howpublished = {UGAF Green IT School / University of Oslo},
	year = {2013},
	abstract = {UGAF Green IT School / University of Oslo, 7 - 11 October 2013},
	author = {Zhang, Yan}
}
@article {24488,
	title = {Modeling Event-Driven Safety Messages Delivery in IEEE 802.11p/WAVE Vehicular Networks},
	journal = {IEEE Communications Letters },
	volume = {17},
	year = {2013},
	pages = {2392-2395},
	publisher = {IEEE},
	author = {Campolo, C. and Molinaro, A. and Vinel, Alexy and Zhang, Yan}
}
@article {Simula.simula.2414,
	title = {Securing Vehicle-to-Grid Communications in the Smart Grid},
	journal = {IEEE Wireless Communications},
	volume = {20},
	number = {6},
	year = {2013},
	pages = {66-73},
	author = {Zhang, Yan and Gjessing, Stein and Liu, H. and Ning, H. and Yang, L. and Guizani, M.}
}
@article {Simula.simula.1754,
	title = {Security and Efficiency in Roaming Services for Wireless Networks: Challenges, Approaches and Prospects},
	journal = {IEEE Communications Magazine},
	volume = {51},
	number = {2},
	year = {2013},
	pages = {142-150},
	author = {He, D. and Chen, C. and Chan, S. and Bu, J. and Zhang, Yan}
}
@article {Simula.simula.1752,
	title = {Sensing-Energy Tradeoff in Cognitive Radio Networks With Relays},
	journal = {IEEE Systems Journal},
	volume = {7},
	number = {1},
	year = {2013},
	pages = {68-76},
	author = {Huang, S. and Chen, H. and Zhang, Yan and Chen, H.}
}
@article {Simula.simula.1570,
	title = {Sensing-Performance Tradeoff in Cognitive Radio Enabled Smart Grid},
	journal = {IEEE Transactions on Smart Grid},
	volume = {4},
	number = {1},
	year = {2013},
	pages = {302-310},
	abstract = {Smart grid is widely considered to be the next generation of power grid, where power generation, management, transmission, distribution and utilization are fully upgraded to improve agility, reliability, efficiency, security, economy and environmental friendliness. Demand Response Management (DRM) is recognized as a control unit of smart grid, with the attempt to balance the real-time load as well as to shift the peak-hour load. Communications are critical to the accuracy and optimality of DRM, and hence at the core of the control performance of smart grid. In this paper, we introduce cognitive radio into smart grid to improve the communication quality. By means of spectrum sensing and channel switching, smart meters can decide to transmit data on either an original unlicensed channel or an additional licensed channel, so as to reduce the communication outage. Considering the energy cost taxed by spectrum sensing together with the control performance degradation incurred by imperfect communications, we formulate the sensing-performance tradeoff problem between better control performance and lower communication cost, paving the way towards green smart grid. The impact of the communication outage on the control performance of DRM is also analyzed, which reduces the profit of power provider and the social welfare of smart grid, although it may not always decrease the profit of power consumer. By employing the energy detector, we prove that there exists a unique optimal sensing time which yields the maximum tradeoff revenue, under the constraint that the licensed channel is sufficiently protected. Numerical results are provided to validate our theoretical analysis.},
	author = {Deng, Ruilong and Chen, Jiming and Cao, Xianghui and Zhang, Yan and Maharjan, Sabita and Gjessing, Stein}
}
@article {Simula.simula.2416,
	title = {Toward Cloud-Based Vehicular Networks With Efficient Resource Management},
	journal = {IEEE Network Magazine},
	volume = {27},
	number = {5},
	year = {2013},
	pages = {48-55},
	author = {Yu, Rong and Zhang, Yan and Gjessing, Stein and Xia, W. and Yang, K.}
}
@misc {Simula.simula.2422,
	title = {Wireless Communications for Smart Grid},
	howpublished = {Green Wireless Communications - Newcom$\#$ Summer School},
	year = {2013},
	abstract = {Smart grid is the next-generation power grid that will be realized with proactive usage of state-of-the-art technologies in the areas of communications, control, and computing. Greenness is one of the major motivations to develop and analyze smart grid. In a smart power grid, a wireless communications architecture plays a crucial role in improving energy-efficiency, sustainability, and stability. This lecture opens by the introduction of smart power grid models and key concepts (e.g., microgrid, renewable energy resources, Vehicle-to-Grid). Then, we focus on smart grid area networks, including HAN, NAN, FAN, and WAN. Next, the lecture discusses different wireless communications technologies for the smart grid, including wireless sensor networks, machine-to-machine, cognitive radio, and long-range cellular networks. For each wireless communication technology, we will present its advantages, disadvantages, and applications in the smart grid. Finally, we present some recent research advances on communications support for demand response management for efficient power load scheduling.},
	author = {Zhang, Yan}
}
@article {Simula.simula.1758,
	title = {Aggregated-Proofs Based Privacy-Preserving Authentication for V2G Networks in Smart Grid},
	journal = {IEEE Transactions on Smart Grid},
	volume = {3},
	number = {4},
	year = {2012},
	month = {december},
	pages = {1722-1733},
	author = {Liu, H. and Ning, H. and Zhang, Yan and Yang, L.}
}
@article {Simula.simula.942,
	title = {Characterizing the Gaming Traffic of World of Warcraft: From Game Scenarios to Network Access Technologies},
	journal = {IEEE Network Magazine},
	volume = {26},
	number = {1},
	year = {2012},
	month = {Jan.},
	pages = {27-34},
	publisher = {IEEE},
	author = {Wang, X. and Kwon, T. and Choi, Y. and Chen, M. and Zhang, Yan}
}
@article {Simula.simula.1378,
	title = {Cognitive Machine-to-Machine Communications: Visions and Potentials for the Smart Grid},
	journal = {IEEE Network Magazine},
	volume = {26},
	number = {3},
	year = {2012},
	month = {May-June},
	pages = {6-13},
	abstract = {Based upon cognitive radio technology, we propose a new Machine-to-Machine (M2M) communications paradigm, namely Cognitive M2M (CM2M) communication. We first motivate the use of cognitive radio technology in M2M communications from different point of views, including technical, applications, industry support, and standardization perspectives. Then, our CM2M network architecture and cognitive machine model are presented and the CM2M systems coexistence in TV white spaces is discussed. After that, a CM2M communications architecture for the smart grid is presented, for which we also propose an energy-efficiency driven spectrum discovery scheme. Numerical results demonstrate significant energy saving and the reliability in supporting data transmissions in the smart grid.},
	author = {Zhang, Yan and Yu, Rong and Nekovee, M. and Liu, Y. and Xie, Shengli and Gjessing, Stein}
}
@article {Simula.simula.944,
	title = {A Cross-Layer Approach for Prioritized Frame Transmissions of MPEG-4 Over the IEEE 802.11 and IEEE 802.11e Wireless Local Area Network},
	journal = {IEEE Systems Journal},
	volume = {5},
	number = {4},
	year = {2012},
	pages = {474-485},
	author = {Xiao, Y. and Zhang, Yan and Nolen, M. and Deng, H. and Zhang, Jin}
}
@article {24506,
	title = {Dual cryptography authentication protocol and its security analysis for radio frequency identification systems},
	journal = {Concurrency and Computation: Practice and Experience},
	volume = {24},
	year = {2012},
	pages = {2040-2054},
	publisher = {John Wiley \& Sons},
	author = {Ning, Huansheng and Liu, Hong and Laurence T. {Yang} and Zhang, Yan}
}
@article {24509,
	title = {Energy-Efficient Cooperative Spectrum Sensing with Amplify-and-Forward Relaying},
	journal = {IEEE Communications Letters },
	volume = {16},
	year = {2012},
	pages = {450-453},
	publisher = {IEEE},
	author = {Huang, S. and Chen, H. and Zhang, Yan and Zhao, F.}
}
@article {Simula.simula.954,
	title = {Modelling Prioritized Broadcasting in Multi-Channel Vehicular Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {61},
	number = {2},
	year = {2012},
	month = {Feb.},
	pages = {687-701},
	author = {Campolo, C. and Molinaro, A. and Vinel, A. and Zhang, Yan}
}
@article {Simula.simula.956,
	title = {Optimal Power Allocation for Spectrum Sensing and Data Transmission in Cognitive Relay Networks},
	journal = {IEEE Wireless Communications Letters},
	volume = {1},
	number = {1},
	year = {2012},
	month = {Feb},
	pages = {26-29},
	author = {Huang, S. and Chen, H. and Zhang, Yan}
}
@article {Simula.simula.1760,
	title = {The Peer{\textquoteright}s Dilemma: a General Framework to Examine Cooperation in Pure Peer-to-Peer Systems},
	journal = {Computer Networks},
	volume = {56},
	number = {17},
	year = {2012},
	month = {November},
	pages = {3756-3766},
	author = {Palomar, Esther and Alcaide, Almudena and Ribagordaa, Arturo and Zhang, Yan}
}
@article {Simula.simula.1370,
	title = {Secondary Users Cooperation in Cognitive Radio Networks: Balancing Sensing Accuracy and Efficiency},
	journal = {IEEE Wireless Communications},
	volume = {19},
	number = {2},
	year = {2012},
	pages = {30-37},
	abstract = {Cooperative spectrum sensing is a promising technique in cognitive radio networks by exploiting multi-user diversity to mitigate channel fading. Cooperative sensing is traditionally employed to improve the sensing accuracy while the sensing efficiency has been largely ignored. However, both sensing accuracy and efficiency have very significant impacts on the overall system performance. In this article, we first identify the fundamental trade-off between sensing accuracy and efficiency in spectrum sensing in cognitive radio networks. Then, we present several different cooperation mechanisms, including sequential, full-parallel, semi-parallel, synchronous, and asynchronous cooperative sensing schemes. The proposed cooperation mechanisms and the sensing accuracy-efficiency trade-off in these schemes are elaborated and analyzed with respect to a new performance metric achievable throughput, which simultaneously considers both transmission gain and sensing overhead. Illustrative results indicate that parallel and asynchronous cooperation strategies are able to achieve much higher performance, compared to existing and traditional cooperative spectrum sensing in cognitive radio networks.},
	author = {Yu, Rong and Zhang, Yan and Liu, Y. and Xie, Shengli and Song, L. and Guizani, M.}
}
@article {24526,
	title = {Secure Service Provision in Smart Grid Communications},
	journal = {IEEE Communications Magazine},
	volume = {50},
	year = {2012},
	pages = {53-61},
	publisher = {IEEE},
	author = {He, D. and Chen, C. and Chan, S. and Zhang, Yan and Bu, J. and Guizani, M.}
}
@article {Simula.simula.1762,
	title = {A Two-Dimensional Architecture for End-to-End Resource Management in Virtual Network Environments},
	journal = {IEEE Network Magazine},
	volume = {26},
	number = {5},
	year = {2012},
	pages = {8-14},
	author = {Wang, N. and Zhang, Yan and Serrat, J. and Gorricho, J. and Guo, T. and Hu, Z. and Zhang, P.}
}
@article {Simula.simula.950,
	title = {Cognitive Radio Based Hierarchical Communications Infrastructure for Smart Grid},
	journal = {IEEE Network Magazine},
	volume = {25},
	number = {5},
	year = {2011},
	month = {Sept/Oct.},
	author = {Yu, Rong and Zhang, Yan and Gjessing, Stein and Chau, Y. and Xie, Shengli and Guizani, M.}
}
@inproceedings {Simula.simula.870,
	title = {Distributed Spectrum Sensing in Cognitive Radio Networks With Fairness Consideration: Efficiency of Correlated Equilibrium},
	journal = {IEEE 8th International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS)},
	year = {2011},
	month = {October},
	pages = {540-549},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Cooperative spectrum sensing improves the relia- bility of detection. However, if the secondary users are selfish, they may not collaborate for sensing. In order to address this problem, Medium Access Control (MAC) protocols can be designed to enforce cooperation among secondary users for spectrum sensing. In this paper, we investigate this problem using game theoretical framework. We introduce the concept of correlated equilibrium for the cooperative spectrum sensing game among non-cooperative secondary users and formulate the optimization problem for the case where secondary users have heterogeneous traffic dynamics. We show that the correlated equilibrium improves the system utility, as compared to the mixed strategy Nash equilibrium. While maximizing system payoff is important, fairness is also equally important in systems with dissimilar users. In order to address fairness issue, we propose a new fair social welfare correlated equilibrium, which maximizes the system utility and ensures that the less well-off users do not starve. We employ a no-regret learning algorithm for distributed implementation of the correlated equilibrium. Finally, we propose a neighbourhood based learning algorithm and show that it achieves better performance than the no-regret algorithm.},
	keywords = {Conference},
	isbn = {978-0-7695-4469-4},
	author = {Maharjan, Sabita and Zhang, Yan and Yuen, Chau and Gjessing, Stein},
	editor = {IEEE, }
}
@article {Simula.simula.265,
	title = {Economic Approaches for Cognitive Radio Networks: a Survey},
	journal = {Wireless Personal Communications},
	volume = {57},
	number = {1},
	year = {2011},
	note = {Special issue on Cognitive Radio Networks and Communications},
	month = {March},
	pages = {33-51},
	abstract = {Efficient resource allocation is one of the key concerns of implementing cognitive radio networks. Game theory has been extensively used to study the strategic interactions between primary and secondary users for effective resource allocation. The concept of spectrum trading has introduced a new direction for the coexistence of primary and secondary users through economic benefits to primary users. The use of price theory and market theory from economics has played a vital role to facilitate economic models for spectrum trading. So, it is important to understand the feasibility of using economic approaches as well as to realize the technical challenges associated with them for implementation of cognitive radio networks. With this motivation, we present an extensive summary of the related work that use economic approaches such as game theory and/or price theory/market theory to model the behavior of primary and secondary users for spectrum sharing and discuss the associated issues. We also propose some open directions for future research on economic aspects of spectrum sharing in cognitive radio networks.},
	doi = {10.1007/s11277-010-0005-9},
	author = {Maharjan, Sabita and Zhang, Yan and Gjessing, Stein}
}
@inbook {Simula.simula.1572,
	title = {Economic Approaches in Cognitive Radio Networks},
	booktitle = {Cognitive Radio Mobile Ad Hoc Networks},
	year = {2011},
	pages = {403-432},
	publisher = {Springer},
	organization = {Springer},
	chapter = {16},
	isbn = {978-1-4419-6171-6},
	author = {Maharjan, Sabita and Zhang, Yan and Gjessing, Stein},
	editor = {Yu, Richard}
}
@article {Simula.simula.247,
	title = {Energy-Efficient and Reliability-Driven Cooperative Communications in Cognitive Body Area Networks},
	journal = {Mobile Networks and Applications},
	volume = {16},
	number = {6},
	year = {2011},
	pages = {733-744},
	author = {Yu, Rong and Zhang, Yan and Chen, G. and Huang, C. and Gao, R.}
}
@article {Simula.simula.940,
	title = {Energy-Efficient Spectrum Discovery for Cognitive Radio Green Networks},
	journal = {Mobile Networks and Applications},
	volume = {17},
	number = {1},
	year = {2011},
	pages = {64-74},
	publisher = {Springer},
	author = {Liu, Y. and Xie, Shengli and Zhang, Yan and Yu, Rong and Leung, V.}
}
@article {Simula.simula.936,
	title = {Home M2M Networks: Architectures, Standards, and QoS Improvement},
	journal = {IEEE Communications Magazine},
	volume = {49},
	number = {4},
	year = {2011},
	month = {April},
	pages = {44-52},
	abstract = {It is envisioned that home networks will shift from the current machine-to-human communications to the machineto-machine (M2M) paradigm with the rapid penetration of embedded devices in home surroundings. In this article, we {fi}rst identify the fundamental challenges in home M2M networks. Then, we present the architecture of home M2M networks that is decomposed into three sub-areas depending on the radio service ranges and potential applications. Finally, we focus on the Quality-of-Service (QoS) management in home M2M networks, considering the increasing number of multimedia devices and growing visual requirements in a home area. Three standards for multimedia sharing and their QoS architectures are outlined. A cross-layer joint admission and rate control design is reported for QoS-aware multimedia sharing. This proposed strategy is aware of the QoS requirement and the resilience of multimedia services. Illustrative results indicate that the joint design is able to intelligently allocate radio bandwidth based on QoS demands in resource-constrained home M2M networks.},
	author = {Zhang, Yan and Yu, Rong and Yao, W. and Xie, Shengli and Xiao, Y. and Guizani, M.}
}
@article {Simula.simula.952,
	title = {An IEEE 802.11p-Based Multi-Channel MAC Scheme With Channel Coordination for Vehicular Ad Hoc Networks},
	journal = {IEEE Transactions on Intelligent Transportation Systems},
	volume = {13},
	number = {2},
	year = {2011},
	pages = {449-458},
	publisher = {IEEE},
	author = {Wang, Q. and Fu, H. and Zhang, Yan}
}
@article {Simula.simula.245,
	title = {Joint Optimization of Power, Packet Forwarding and Reliability in MIMO Wireless Sensor Networks},
	journal = {Mobile Networks and Applications},
	volume = {16},
	number = {6},
	year = {2011},
	pages = {760-770},
	abstract = {In this paper, we study the reliable packet forwarding in Wireless Sensor Networks (WSNs) with the multiple-input multiple-output (MIMO) and orthogonal space time block codes (OSTBC) techniques. The objective is to propose a cross-layer optimized forwarding scheme to maximize the Successful Transmission Rate (STR) while satisfying the given end-to-end power consumption constraint. The channel coding, power allocation, and route planning are jointly considered to significantly improve the transmission quality in terms of STR. The joint optimization design is formulated as a global deterministic optimization and also a local stochastic optimization issues. It is found that the stochastic optimization approach can effectively model, analyze, and solve the routing problem. In order to substantially reduce the implementation complication of the global optimization, we propose a low-complexity distributed scheme. The determination of relaying nodes and power budgets are decoupled, i.e. performing route planning and power allocation separately. We have shown that the result in the distributed scheme is able to provide sufficiently accurate predication of the global optimization. In addition, the proposed scheme can clearly reduce the Symbol Error Rate (SER) and achieve higher STR compared with two existing energy-efficient routing protocols, in which no joint design is considered.},
	doi = {10.1007/s11036-010-0265-3},
	author = {Yu, Rong and Zhang, Yan and Song, L. and Yao, W.}
}
@article {Simula.ND.319,
	title = {Medium Access Control in Vehicular Ad Hoc Networks},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {11},
	number = {7},
	year = {2011},
	pages = {796-812},
	author = {Fu, H. and Wang, Q. and Zhang, Yan}
}
@article {Simula.simula.946,
	title = {Modeling Channel Allocation for Multimedia Transmission Over Infrastructure Based Cognitive Radio Networks},
	journal = {IEEE Systems Journal},
	volume = {5},
	number = {3},
	year = {2011},
	month = {Sept.},
	pages = {417-426},
	publisher = {IEEE},
	doi = {10.1109/JSYST.2011.2159640 },
	author = {Jiang, T. and Wang, H. and Zhang, Yan}
}
@article {Simula.ND.233,
	title = {Optimal Fault-Tolerant Broadcasting in Wireless Mesh Networks},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {11},
	number = {5},
	year = {2011},
	month = {Jan},
	pages = {610-620},
	author = {Xin, Qin and Zhang, Yan and Laurence T. {Yang}}
}
@article {Simula.simula.948,
	title = {Scalable and Distributed Key Array Authentication Protocol in RFID-Based Sensor Systems},
	journal = {IET Communications},
	volume = {5},
	number = {12},
	year = {2011},
	pages = {1755-1768},
	publisher = {IEEE},
	author = {Ning, H. and Liu, H. and Mao, J. and Zhang, Yan}
}
@inproceedings {Simula.simula.868,
	title = {Sensing-Delay Tradeoff for Communication in Cognitive Radio Enabled Smart Grid},
	journal = {2nd IEEE International Conference on Smart Grid Communications - SmartGridComm 2011},
	year = {2011},
	month = {October},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Smart grid is widely considered to be the next gen- eration of power grid, which will be integrated with information feedback communication to improve agility, reliability, efficiency and security. One of the key foundations of smart grid is timely access to meter data via reliable communication infrastructure. In this paper, we introduce cognitive radio into home area networks of smart grid, whose framework and result can be trivially extended to neighborhood and wide area networks. By means of spectrum sensing and channel switching techniques, smart meters can decide to transmit meter data either on the original unlicensed channel or the additional licensed channel, in order to improve reliability and timeliness. We find optimal sensing time to reduce packet loss rate and delay, under the constraint that the PU is sufficiently protected. We formulate the sensing-delay tradeoff problem and prove that it has unique optimal sensing time which yields the minimum delay. Simulation results are provided, which match very well with the theoretical results.},
	isbn = {978-1-4577-1704-8},
	doi = {10.1109/SmartGridComm.2011.6102309},
	author = {Deng, Ruilong and Maharjan, Sabita and Cao, Xianghui and Chen, Jiming and Zhang, Yan and Gjessing, Stein},
	editor = {IEEE, }
}
@article {Simula.nd.457,
	title = {Sleeping Management for Scalable Topology Control in Wireless Sensor Networks},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {11},
	number = {8},
	year = {2011},
	month = {Aug.},
	author = {Yu, Rong and Zhang, Yan and Gao, R. and Song, L.}
}
@article {24497,
	title = {A strong user authentication scheme with smart cards for wireless communications},
	journal = {Computer Communications},
	volume = {34},
	year = {2011},
	pages = {367-374},
	publisher = {Elsevier},
	author = {He, Daojing and Ma, Maode and Zhang, Yan and Chen, Chun and Bu, Jiajun}
}
@article {24492,
	title = {Symbol Error Rate Analysis and Power Allocation for Adaptive Relay Selection Schemes},
	journal = {Wireless Personal Communications},
	volume = {56},
	year = {2011},
	pages = {457-467},
	publisher = {Springer},
	author = {Liu, Tianxi and Song, Lingyang and Jiao, Bingli and Zhang, Yan}
}
@inproceedings {Simula.win.4,
	title = {Admission and Power Control for Cognitive Radio Cellular Networks: a Multidimensional Knapsack Solution},
	journal = {CogART 2010, invited paper},
	year = {2010},
	month = {November},
	publisher = {IEEE},
	type = {Workshop},
	abstract = {Admission and power control schemes play important roles in deploying cognitive radio technology to cellular networks. In this paper, we propose a method to calculate the power scale factor, introduce two pre-admission control schemes, and reformulate the problem as a multidimensional knapsack problem. In addition, we propose a novel admission and power control scheme called JAPC-MKP. Simulation results show that our proposed JAPC-MKP can very closely approach the optimal results from the optimization software MOSEK, and greatly outperform the existing schemes in most cases.},
	isbn = {978-1-4244-8132-3},
	author = {Xiang, Jie and Zhang, Yan and Skeie, Tor},
	editor = {De Sanctis, Mauro}
}
@article {Simula.simula.251,
	title = {Availability-Aware Multimedia Scheduling in Heterogeneous Wireless Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {60},
	number = {3},
	year = {2010},
	pages = {692-703},
	author = {Zhou, L. and Wang, H. and Lian, S. and Zhang, Yan and Athanasios V. {Vasilakos}}
}
@article {Simula.sc.808,
	title = {Computational Vascular {fl}uid-structure Interaction: Methodology and Application to Cerebral Aneurysms},
	journal = {Biomechanics and Modeling in Mechanobiology},
	volume = {9},
	number = {4},
	year = {2010},
	pages = {481-498},
	abstract = {A computational vascular fluid-structure interaction framework for the simulation of patient-specific cerebral aneurysm configurations is presented. A new approach for the computation of the blood vessel tissue prestress is also described. Simulations of four patient-specific models are carried out, and quantities of hemodynamic interest such as wall shear stress and wall tension are studied to examine the relevance of fluid-structure interaction modeling when compared to the rigid arterial wall assumption. We demonstrate that flexible wall modeling plays an important role in accurate prediction of patient-specific hemodynamics. Discussion of the clinical relevance of our methods and results is provided.},
	doi = {10.1007/s10237-010-0189-7},
	author = {Y., Bazilevs and Hsu, M.-C and Zhang, Yan and Wang, W. and Kvamsdal, T. and Hentschel, Susanne and J. G. {Isaksen}}
}
@article {Simula.nd.451,
	title = {Context Aware Cross Layer Optimized Video Streaming in Wireless Multimedia Sensor Networks},
	journal = {The Journal of Supercomputing},
	volume = {54},
	number = {1},
	year = {2010},
	pages = {94-121},
	author = {Shu, L. and Zhang, Yan and Yu, Z. and Yang, L.T and Hauswirth, M. and Xiong, N.}
}
@article {Simula.simula.1192,
	title = {Cross Layer Optimization for Data Gathering in Wireless Multimedia Sensor Networks Within Expected Network Lifetime},
	journal = {Journal of Universal Computer Science},
	volume = {16},
	number = {19},
	year = {2010},
	pages = {1343-1367},
	author = {Shu, L. and Hauswirth, M. and Zhang, Yan and Ma, J. and Min, G. and Wang, Y.}
}
@article {Simula.nd.453,
	title = {Cross-Layer Optimized Call Admission Control in Cognitive Radio Networks},
	journal = {Mobile Networks and Applications},
	volume = {15},
	number = {5},
	year = {2010},
	pages = {610-626},
	author = {Yu, Rong and Zhang, Yan and Huang, M. and Xie, Shengli}
}
@inproceedings {Simula.simula.524,
	title = {Delay Reduction for Real Time Services in IEEE 802.22 Wireless Regional Area Network},
	journal = {The 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2010)},
	year = {2010},
	month = {September 2010},
	pages = {1836-1841},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Real time traffic such as voice and video have strict requirements on the acceptable end-to-end packet delay. When there are different types of traffic with different requirements on tolerable latency, priority based packet scheduling schemes are normally used in order to reduce the queuing delay for real time services. However, in cognitive radio networks, the time that the system spends on spectrum sensing adds further delay to the packet transmission. In this paper, we propose a new scheme to significantly reduce the overall packet delay, including the delay due to sensing for real time services in cognitive radio networks. We derive the expression for average packet delay for the proposed scheme and the simulation results match well with the analytical results. The numerical results show that the priority based scheduling scheme combined with our scheme substantially reduces the packet delay for real time applications.},
	isbn = {978-1-4244-8017-3},
	doi = {10.1109/PIMRC.2010.5671631},
	author = {Maharjan, Sabita and Xiang, Jie and Zhang, Yan and Gjessing, Stein},
	editor = {IEEE, }
}
@article {Simula.simula.249,
	title = {Distributed Media Services in P2P-Based Vehicular Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {60},
	number = {2},
	year = {2010},
	pages = {692-703},
	author = {Zhou, L. and Zhang, Yan and Song, K. and Jing, W. and Athanasios V. {Vasilakos}}
}
@inproceedings {Simula.simula.584,
	title = {Distributed Spectrum Sensing for Cognitive Radio Networks With Heterogeneous Traffic (Invited Paper)},
	journal = {3rd International Workshop on Cognitive Radio and Advanced Spectrum Management},
	year = {2010},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Cooperative spectrum sensing improves reliability and the detection performance of sensing. However, the fully cooperative scenario may not be realistic to assume in many cases. We consider a cognitive radio network with heavy traffic users and light traffic users and analyze their behavior towards sensing using the concept of mixed strategy Nash equilibrium. Further, we design a distributed game using evolutionary game theory such that as long as light traffic users are present, they share the sensing responsibility while heavy traffic users get a free ride. Finally, the evolution dynamics is shown to converge to the evolutionarily stable strategy for the case of multiple users.},
	isbn = {978-1-4244-8132-3},
	author = {Maharjan, Sabita and Zhang, Yan and Gjessing, Stein},
	editor = {IEEE, }
}
@article {Simula.win.6,
	title = {Downlink Spectrum Sharing for Cognitive Radio Femtocell Networks},
	journal = {IEEE Systems Journal},
	volume = {4},
	number = {4},
	year = {2010},
	note = {Special issue on Broadband Access Networks},
	month = {December},
	pages = {524-534},
	abstract = {Femtocell is envisioned as a highly promising solution for indoor wireless communications. The spectrum allocated to femtocells is traditionally from the same licensed spectrum bands of macrocells. In this case, the capacity of femtocell networks is highly limited due to the finite number of licensed spectrum bands and also the interference with macrocells and other femtocells. In this paper, we propose a radically new communication paradigm by incorporating cognitive radio in femtocell networks. The cognitive radio enabled femtocells are able to access spectrum bands not only from macrocells but also from other licensed systems (e.g. TV systems) provided the interference from femtocells to the existing systems is not harmful. It results in more channel opportunities for femtocells. Thus, the co-channel interference in femtocells can be greatly reduced and the network capacity can be significantly improved. Because of the difference from other traditional wireless networks, we argue the traditional spectrum sharing schemes such as coloring methods are not efficient to femtocell networks especially for dense deployment scenarios. We formulate the downlink spectrum sharing problem in cognitive radio femtocell networks, and employ decomposition theories to solve the problem. Simulation results indicate that cognitive radio enabled femtocells could achieve much higher capacity than the femtocell networks which do not employ agile spectrum access. Simulation results also show that our proposed scheme without any iteration can achieve almost twice of the average capacity by coloring method when the number of available channels is less than five. Moreover, our proposed scheme can converge very fast with a typical value of only five iterations, and it can achieve around two percent extra average capacity than the fixed power control scheme.},
	doi = {10.1109/JSYST.2010.2083230},
	author = {Xiang, Jie and Zhang, Yan and Skeie, Tor and Xie, Lang}
}
@inproceedings {Simula.ND.403,
	title = {Energy Minimization Approach for Optimal Cooperative Spectrum Sensing in Sensor-Aided Cognitive Radio Networks},
	journal = {2010 The 5th Annual ICST Wireless Internet Conference (WICON 2010)},
	year = {2010},
	publisher = {ICST/Create-Net},
	type = {Conference},
	abstract = {In a sensor-aided cognitive radio network, collaborating battery-powered sensors are deployed to aid the network in cooperative spectrum sensing. These sensors consume energy for spectrum sensing and therefore deplete their life-time, thus we study the key issue in minimizing the sensing energy consumed by such group of collaborating sensors. The IEEE P802.22 standard specifies spectrum sensing accuracy by the detection and false alarm probabilities, hence we address the energy minimization problem under this detection accuracy constraint. Firstly, we derive the bounds for the number of sensors to simultaneously guarantee the thresholds for high detection probability and low false alarm probability. With these bounds, we then formulate the optimization problem to find the optimal sensing interval and the optimal number of sensor that minimize the energy consumption. Thirdly, the approximated analytical solutions are derived to solve the optimization accurately and efficiently in polynomial time. Finally, numerical results show that the minimized energy is significantly lower than the energy consumed by a group of randomly selected sensors. The mean absolute error of the approximated optimal sensing interval compared with the exact value is less than 4\% and 8\% under good and bad SNR conditions, respectively. The approximated optimal number of sensors is shown to be very close to the exact number.},
	isbn = {978-963-9799-86-8},
	author = {Hai Ngoc {Pham} and Zhang, Yan and Paal Einar {Engelstad} and Skeie, Tor and Eliassen, Frank},
	editor = {Mahmoud Daneshmand {Chen}}
}
@article {Simula.nd.449,
	title = {A Fast Formation Flocking Scheme for a Group of Interactive Distributed Mobile Nodes in Autonomous Networks},
	journal = {Mobile Networks and Applications},
	volume = {8},
	number = {9},
	year = {2010},
	pages = {477-487},
	author = {Xiong, N. and Zhang, Yan and Yang, L.T and Yeo, S. and Shu, L. and Yang, F.}
}
@article {Simula.simula.240,
	title = {Feedback Based Clock Synchronization in Wireless Sensor Networks: a Control Theoretic Approach},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {59},
	number = {6},
	year = {2010},
	month = {July},
	pages = {2963-2973},
	author = {Chen, J. and Yu, Q. and Zhang, Yan and Chen, H. and Sun, Y.}
}
@inproceedings {Simula.simula.255,
	title = {A Group-Based Cooperative Medium Access Control Protocol for Cognitive Radio Networks},
	journal = {Proceedings of the 18th International Workshop on Quality of Service (IWQoS), 2010},
	year = {2010},
	publisher = {IEEE Press},
	type = {Conference},
	isbn = {978-1-4244-5987-2},
	author = {Liu, Y. and Yu, Rong and Zhang, Yan and Xie, Shengli},
	editor = {B., Liu}
}
@article {Simula.nd.443,
	title = {Handoff Performance in Wireless Mobile Networks With Unreliable Fading Channel},
	journal = {IEEE Transactions on Mobile Computing},
	volume = {9},
	number = {2},
	year = {2010},
	pages = {188-200},
	author = {Zhang, Yan}
}
@article {Simula.simula.1194,
	title = {Joint Admission and Rate Control for Multimedia Sharing in Wireless Home Networks},
	journal = {Computer Communications},
	volume = {33},
	number = {14},
	year = {2010},
	pages = {1632-1644},
	author = {Yu, Rong and Zhang, Yan and Huang, C. and Gao, R.}
}
@article {Simula.ND.383,
	title = {Medium Access Control Protocols in Cognitive Radio Networks},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {10},
	number = {1},
	year = {2010},
	note = {Special issue on Recent Advances in Wireless Communications and Networks},
	month = {January},
	pages = {31-49},
	abstract = {In cognitive radio (CR) networks, medium access control (MAC) protocols play an important role to exploit the spectrum opportunities, manage the interference to primary users (PUs), and coordinate the spectrum access amongst secondary users (SUs). In this paper, we first introduce the challenges in the design and implementation of CR MAC protocols. Then, we make a comprehensive survey of the state-of-the-art CR MAC protocols and categorize them on the basis of spectrum sharing modes, i.e., overlay and underlay modes. We also introduce some other classification metrics such as architecture (centralized or distributed), sharing behaviors (cooperative or non-cooperative), and access modes (contention based or contention free). Through the study, we find out that most CR MAC protocols are designed for the overlay mode. The CR MAC protocols in underlay mode could yield higher spectrum utilization efficiency with the cost of more complicated power and admission control schemes. The centralized CR MAC protocols are more suitable to do spectrum sensing using quiet period of whole network, while the distributed CR MAC protocols are more flexible to deploy. We identify several future directions, such as more practical CR MAC protocols for underlay mode, MAC protocols considering security, MAC protocols considering heterogeneous coexistence, etc.},
	doi = {10.1002/wcm.906},
	author = {Xiang, Jie and Zhang, Yan and Skeie, Tor}
}
@article {Simula.simula.243,
	title = {A Parallel Cooperative Spectrum Sensing in Cognitive Radio Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {59},
	number = {8},
	year = {2010},
	month = {Oct.},
	pages = {4079-4092},
	author = {Xie, Shengli and Liu, Y. and Zhang, Yan and Yu, Rong}
}
@article {Simula.ND.315,
	title = {QoS-Aware Packet Forwarding in MIMO Sensor Networks: a Cross-Layer Approach},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {10},
	number = {6},
	year = {2010},
	pages = {748-757},
	author = {Song, L. and Zhang, Yan and Yu, Rong and Yao, W.}
}
@inproceedings {Simula.netsys.20,
	title = {Reliable Channel Selection and Routing for Real-Time Services Over Cognitive Radio Mesh Networks},
	journal = {Qshine 2010},
	year = {2010},
	publisher = {ACM},
	type = {Conference},
	abstract = {In Cognitive Radio Mesh Networks (CogMesh), Secondary Mesh Routers (SMRs) can opportunistically utilize the licensed spectrums for the traffic of the Secondary Mesh Users (SMUs). How to guarantee Quality of Service (QoS) for real-time services over CogMesh is still an opening issue. In this paper, we present a discrete-time vacation queueing system to abstract the Primary User (PU) interruption to SMR data transmission. Moreover, we formulate the optimization problem of joint channel selection and routing, to achieve minimum end-to-end delay for SMR while guaranteeing the channel unavailability. A heuristic method is proposed to solve this problem and results show our proposed method performs the most close to the optimal scheme, and outperforms the minimal unavailability scheme and minimal delay scheme in terms of end-to-end delay and solution rate.},
	author = {Xie, Lang and Poul E. {Heegaard} and Zhang, Yan and Xiang, Jie},
	editor = {Zhang, Xi}
}
@article {Simula.nd.445,
	title = {A Resilient and Scalable Flocking Scheme in Autonomous Vehicular Networks},
	journal = {Mobile Networks and Applications},
	volume = {15},
	number = {1},
	year = {2010},
	pages = {126-136},
	author = {Xiong, N. and Athanasios V. {Vasilakos} and Yang, L.T and Pedrycz, W. and Zhang, Yan and Li, Y.}
}
@article {Simula.simula.1196,
	title = {TPGF: Geographic Routing in Wireless Multimedia Sensor Networks},
	journal = {Telecommunication Systems},
	volume = {44},
	number = {1},
	year = {2010},
	pages = {79-95},
	author = {Shu, L. and Zhang, Yan and Yang, L. and Wang, Y. and Hauswirth, M. and Xiong, N.}
}
@article {Simula.simula.1208,
	title = {Waiting Time in Block Fading MIMO Systems With Dynamic-Depth Interleaving},
	journal = {Science China Information Sciences},
	volume = {53},
	number = {8},
	year = {2010},
	pages = {1622-1627},
	author = {Guo, H. and Hu, H. and Zhang, Yan}
}
@article {Simula.ND.313,
	title = {Adaptive Space-Time Diversity Slotted ALOHA Over 2*m MIMO Multi-Access Channels},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {58},
	number = {7},
	year = {2009},
	pages = {3271-3282},
	author = {Guo, H. and Hu, H. and Zhang, Yan and Chen, H.}
}
@inproceedings {Simula.ND.347,
	title = {Almost Optimal Distributed M2M Multicasting in Wireless Mesh Networks},
	journal = {Proceedings of the 6th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2009)},
	year = {2009},
	publisher = {IEEE},
	type = {1},
	isbn = {978-1-4244-5113-5},
	author = {Xin, Qin and Manne, Fredrik and Zhang, Yan and Wang, Jianping and Zheng, Zeyu}
}
@article {Simula.ND.131,
	title = {Call Admission Control Algorithms in OFDM-Based Wireless Multiservice Networks},
	journal = {Wireless Personal Communications},
	volume = {50},
	number = {1},
	year = {2009},
	pages = {99-104},
	publisher = {Springer},
	author = {Zhang, Yan and Chen, Y. and He, J. and Wang, C. and Athanasios V. {Vasilakos}}
}
@inproceedings {Simula.ND.257,
	title = {Cross-Layer Optimized Routing for Wireless Sensor Networks Using Dynamic Programming},
	journal = {the IEEE International Conference on Communications (ICC), ICC 2009},
	year = {2009},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-3435-0},
	author = {Song, L. and Zhang, Yan and Yu, Rong and Yao, W.},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.405,
	title = {Dynamic Spectrum Sharing in Cognitive Radio Femtocell Networks},
	journal = {2009 Fourth International Conference on Access Networks (ACCESSNETS 2009), invited paper},
	volume = {37},
	year = {2009},
	month = {November},
	pages = {164-178},
	publisher = {Springer},
	type = {Conference},
	abstract = {Femtocell is envisioned as a highly promising solution to tackle the communications in the indoor environments, which has been a very challenging problem for mobile network operators. Currently, the spectrum allocated to femtocells is from the same licensed spectrum of macrocells, and the same mobile network operator. In this case, the capacity of femtocell networks may be largely limited due to the finite number of licensed spectrum bands and also the interference with other femtocells and macrocells. In this paper, we propose a radically new communications paradigm by incorporating cognitive radio in femtocell networks (COGFEM). In COGFEM, the cognitive radio enabled femtocells are able to access licensed spectrum bands not only from macrocells but also from other licensed systems (e.g. TV systems). Thus, the co-channel interference in femtocells can be greatly reduced and the network capacity can be significantly improved. We formulate a joint channel allocation and power control problem in COGFEM, and present two intelligent algorithms for efficient spectrum sharing in COGFEM. Results indicate that COGFEM is able to achieve much higher capacity than the femtocell networks which does not employ agile spectrum access.},
	isbn = {978-3-642-11663-6},
	author = {Xiang, Jie and Zhang, Yan and Skeie, Tor},
	editor = {Xiao Jun {Hei} and Cheung, Lawrence}
}
@article {Simula.ND.239,
	title = {An Energy Efficient Cross Layer Protocol of Channel-Aware Geographic-Informed Forwarding in Wireless Sensor Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {58},
	number = {6},
	year = {2009},
	pages = {3041-3052},
	author = {Zhang, L. and Zhang, Yan}
}
@article {Simula.ND.255,
	title = {Energy Management Analysis and Enhancement in IEEE 802.16e WirelessMAN},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {58},
	number = {7},
	year = {2009},
	pages = {3738-3752},
	publisher = {IEEE Transactions on Vehicular Technology},
	author = {Zhang, Yan and Xiao, Y. and Leung, V.}
}
@article {Simula.nd.447,
	title = {On Hierarchical Pipeline Paging in Multi-Tier Overlaid Hierarchical Cellular Networks},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {8},
	number = {9},
	year = {2009},
	pages = {4406-4410},
	author = {Xiao, Y. and Chen, H. and Du, X. and Zhang, Yan and Chen, H. and Guizani, M.}
}
@article {Simula.ND.195,
	title = {Intrinsic Measure of Diversity Gains in Generalized Distributed Antenna Systems With Cooperative Users},
	journal = {IET Communications},
	volume = {3},
	number = {2},
	year = {2009},
	pages = {209-222},
	author = {Chen, Y. and Hu, L. and Yuen, C. and Zhang, Yan and Zhang, Z. and Rapajic, P.}
}
@inproceedings {Simula.ND.253,
	title = {Joint Bandwidth Reservation and Admission Control in IEEE 802.16e Based Networks},
	journal = {the IEEE International Conference on Communications (ICC 2009)},
	year = {2009},
	month = {June},
	pages = {1-6},
	publisher = {IEEE},
	type = {Conference},
	abstract = {The IEEE 802.16e is a compatible and reasonable technology to solve the last mile access problem. Since the multiple services in the system are connection-oriented, it is crucial to provide effective admission control and resource allocation mechanisms to guarantee the Quality of Service (QoS) of the system. In this paper, we investigate the joint bandwidth reservation and admission control in the IEEE 802.16e networks. Foremost, we consider two system models: model without buffer and model with buffer. Then two optimization problems are formulated for the two models separately. To solve the two min-max optimization problems, we propose a bandwidth reservation algorithm. In addition, the bandwidth reservation thus obtained can be used with admission control jointly. Our aim is to enhance fairness while satisfying QoS requirement. Numerical results are presented to demonstrate the performance of the proposed scheme in terms of maximal call blocking probability and fairness.},
	keywords = {Conference},
	isbn = {978-1-4244-3435-0},
	doi = {10.1109/ICC.2009.5199109},
	author = {Xie, Lang and Xiang, Jie and Zhang, Yan and Zhang, Jin},
	editor = {Akhavan, Hamid}
}
@inproceedings {Simula.ND.281,
	title = {Minimum-Latency Gossiping in Multi-Hop Wireless Mesh Networks},
	journal = {Proceedings of the IEEE 44th International Conference on Communications (ICC{\textquoteright}09)},
	year = {2009},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Wireless Mesh Networks (WMNs) is an emerging communication paradigm to enable resilient, cost-efficient and reliable services for the future-generation wireless networks. We study the minimum-latency communication primitive of gossiping (all-to-all communication) in multi-hop ad-hoc WMNs. Each mesh node in the WMN is initially given a message and the objective is to design a minimum-latency schedule such that each mesh node distributes its message to all other mesh nodes. Minimum-latency gossiping problem is known to be NP-hard even for the scenario in which the topology of the WMN is known to all mesh nodes in advance. We show an approximation scheme that can complete gossiping task in O(n{\l}og^{\frac{3}{2}} n) time units with high probability at least 1-\frac{1}{n} in any ad-hoc WMN of size n. Our algorithm allows the labels (identifiers) of the mesh nodes to be polynomially large in n. To the best of our knowledge, this is the first time that randomized algorithm has been considered in ad-hoc WMNs with large labels. Moreover, our gossiping scheme also significantly improved all current gossiping algorithms in terms of approximation ratio. Our work has approximation ratio at most O({\l}og^{\frac{3}{2}} n) which is a great improvement of the current best known state-of-the-art algorithm with approximation ratio O({\l}og^2 n) but for linearly large node labels by Czumaj and Rytter \cite{CR03} [FOCS\&$\#$39;03].},
	isbn = {978-1-4244-3435-0},
	author = {Xin, Qin and Zhang, Yan and Xiang, Jie}
}
@inbook {Simula.ND.279,
	title = {Network Reconfiguration in High-Performance Interconnection Networks},
	booktitle = {Autonomic Computing and Networking},
	year = {2009},
	pages = {313-332},
	publisher = {Springer},
	organization = {Springer},
	chapter = {8},
	abstract = {High-performance interconnection networks like InfiniBand, ASI, Autonet andMyrinet have the property of link level flow control. As such alterating the routing function while the network is operational is a complex process, because the danger of packet deadlocks must be addressed. Over the last 5-6 years this problem has been addressed and solved by the research community. This chapter collects several proposals for updating a routing function in interconnection networks after the occurrence of a topological change. Both traditional and recent reconfiguration schemes are covered, and the selection includes both technology-dependant and generic techniques.},
	isbn = {978-0-387-89827-8},
	author = {Casado, Rafael and Berm{\'u}dez, Aurelio and Robles-Gomez, Antonio and Lysne, Olav and Skeie, Tor and {\r A}shild Gr{\o}nstad {Solheim} and S{\o}dring, Thomas},
	editor = {Mieso K. {Denko} and Laurence Tianruo {Yang} and Zhang, Yan}
}
@article {Simula.ND.135,
	title = {A Novel K-Hop Compound Metric Based Clustering Scheme for Ad Hoc Wireless Networks},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {8},
	number = {1},
	year = {2009},
	pages = {367-375},
	author = {Zhang, Yan and Chen, H. and Zhang, L. and Liu, K.}
}
@inproceedings {Simula.ND.377,
	title = {Optimal Cooperative Spectrum Sensing in Cognitive Sensor Networks},
	journal = {The 5th International Wireless Communications and Mobile Computing Conference (IWCMC {\textquoteright}09)},
	year = {2009},
	pages = {1073-1079},
	publisher = {ACM New York, NY, USA},
	type = {Conference},
	abstract = {This paper addresses the problem of optimal cooperative spectrum sensing in a cognitive-enabled sensor network where cognitive sensors can cooperate in the sensing of the spectrum. Such sensor networks are assumed to be power resource constrained. With a given threshold for the accuracy of the spectrum detection, we find the optimal number of cognitive sensors participating in the cooperative spectrum sensing and the optimal sensing interval that minimize the total energy consumption of the cooperative sensing. First, the mathematical lower bound and upper bound for the number of cooperative cognitive sensors are found. Then the optimization problem to minimize the total energy consumed by a group of sensors is presented. Finally, an efficient approximate solution to the optimization problem is proposed. Numerical calculations validate the accuracy and the performance of the proposed scheme. The impact of the noise uncertainty, the choice of the energy detection threshold, and the spectrum bandwidth on the detection accuracy and the minimum total energy consumption is also studied.},
	isbn = {978-1-60558-569-7},
	author = {Hai Ngoc {Pham} and Zhang, Yan and Paal Einar {Engelstad} and Skeie, Tor and Eliassen, Frank}
}
@inproceedings {Simula.ND.331,
	title = {Optimal Sensing Cooperation for Spectrum Sharing in Cognitive Radio Networks},
	journal = {European Wireless 2009 (EW 2009)},
	year = {2009},
	month = {May},
	pages = {216-221},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Cognitive radio is a highly promising technology to efficiently solve the spectrum scarcity challenge and harmonize the networks heterogeneity. Through component spectrum sharing, Secondary Users (SUs) are able to opportunistically access licensed spectrum shared with the primary system. In the literature, spectrum sharing is normally investigated on the basis of the assumption that the spectrum sensing is perfect. However, in reality, the spectrum sensing can not be ideal, as demonstrated by two non-zero metrics, probability of misdetection and the probability of false alarm. In this paper, we focus on the interaction between spectrum sensing and spectrum sharing. In particular, we will study the optimization of cooperative spectrum sensing for achieving maximum spectrum utilization in cognitive radio networks. A new percentage rule is proposed for the spectrum sensing cooperation, which is more generic than quantity-based rules and is applicable in both sparse and dense sensing scenarios. An analytical model is presented to analyze the spectrum sharing performance. Numerical examples are presented to show the optimal percentage of cooperating sensors in achieving maximum utilization, which simultaneously achieve minimum blocking probabilities. Results are also shown to explore the impact of key system parameters on the performance metrics.},
	isbn = {978-1-4244-5935-3},
	doi = {10.1109/EW.2009.5357760},
	author = {Zhang, Yan and Xiang, Jie and Xin, Qin and Geir Egil {{\O}ien}},
	editor = {Marcos Katz Frank {Fitzek}}
}
@article {Simula.nd.461,
	title = {Optimization Between AES Security and Performance for IEEE 802.15.3 WPAN},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {8},
	number = {12},
	year = {2009},
	pages = {6030-6037},
	author = {Olteanu, A. and Xiao, Y. and Zhang, Yan}
}
@article {Simula.ND.241,
	title = {Power-Fixed and Power-Aware MAC Protocols for Multi-Hop Wireless Networks With Large Interference Area},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {58},
	number = {6},
	year = {2009},
	pages = {2966-2976},
	author = {Zhang, Yan and Chen, H. and Xiang, Jie and Guizani, M.}
}
@article {Simula.ND.317,
	title = {Protecting Mobile TV Multimedia Content in DVB/GPRS Heterogeneous Wireless Networks},
	journal = {Journal of Universal Computer Science},
	volume = {15},
	number = {5},
	year = {2009},
	pages = {1023-1041},
	author = {Lian, S. and Zhang, Yan}
}
@inbook {Simula.ND.299,
	title = {Providing Resilience in Communications Networks},
	booktitle = {Simula Research Laboratory - by thinking constantly about it},
	year = {2009},
	pages = {163-188},
	publisher = {Springer},
	organization = {Springer},
	chapter = {15},
	address = {Heidelberg},
	abstract = {The purpose of the Resilient Networks Project at Simula is to provide resilience in communications networks with cost-efficient approaches. In particular, we identify and solve challenges for both Internet and wireless networks. In the Internet context, we focus on scalable solutions for maintaining network operations during failures or other challenging scenarios. This includes providing fast recovery from component failures, increasing robustness to failures and traffic fluctuations by spreading traffic on multiple paths, and investigating the scalability limitations of the current interdomain routing protocol BGP. Wireless resilience is highly dependent on a specific kind of wireless system and it is closely related to Quality-of-Service (QoS) provisioning. For this, we have investigated the resilience in resource-constrained sensor networks and QoS in OFDM-based wireless networks. It has been shown that the proposed strategies are able to substantially enhance network throughput and increase service reliability. In this chapter, we give an overview of the recent activities in the project, and briefly discuss future plans. Further technical details can be found in our journal and conference papers.},
	isbn = {978-3-642-01156-6},
	author = {Kvalbein, Amund and Zhang, Yan},
	editor = {Tveito, Aslak and Are Magnus {Bruaset} and Lysne, Olav}
}
@article {Simula.ND.287,
	title = {QoS Aware Admission and Power Control for Cognitive Radio Cellular Networks},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {9},
	number = {11},
	year = {2009},
	month = {November},
	pages = {1520-1531},
	publisher = {Wiley},
	abstract = {In cognitive radio cellular networks, the Secondary Users (SUs) are allowed to access the channels licensed to the Primary Users (PUs) including Primary Transmitters (PTs) and Primary Receivers (PRs), only if the interference to the PRs is less than the predefined threshold, and the Quality of Service (QoS) requirements of PTs are guaranteed. In addition, different SUs may require different levels of QoS, and pay differently depending on the provided QoS. The network operator achieves different secondary revenues by admitting SUs in different QoS levels. The problem we address in this paper is to maximize the total secondary revenue relative to the interference constraints on PRs, and QoS requirements for both PTs and SUs. We formulate this optimization problem, and propose a power control scheme for both PTs and SUs. Then, we introduce three solutions including an exact solution using dynamic programming, a greedy heuristic algorithm, and a minimal SINR removal algorithm. Based on these algorithms, we propose three QoS aware admission and power control schemes, one optimal solution called QAPC-Dynamic, and two approximate solutions called QAPC-Greedy and QAPC-MSRA, respectively. Numerical results show that QAPC-Dynamic always achieves the highest secondary revenue while QAPC-MSRA gives the lowest secondary revenue. Since the time complexity of QAPC-Dynamic is much higher than the other two schemes, QAPC-Greedy is recommended considering the trade-off between the computation complexity and performance gain.},
	doi = {10.1002/wcm.765},
	author = {Xiang, Jie and Zhang, Yan and Skeie, Tor and He, Jianhua}
}
@article {Simula.nd.459,
	title = {QoS Differentiated and Fair Packet Scheduling in Broadband Wireless Access Networks},
	journal = {EURASIP Journal on Wireless Communications and Networking},
	volume = {vol. 2009},
	number = {Article ID 482764},
	year = {2009},
	author = {Yu, Rong and Zhang, Yan and Xie, Shengli}
}
@article {Simula.ND.74,
	title = {Quantitative Analysis of Location Management and QoS in Wireless Networks},
	journal = {Journal of Network and Computer Applications},
	volume = {32},
	number = {2},
	year = {2009},
	pages = {483-489},
	author = {Zhang, Yan and Laurence T. {Yang} and Ma, J. and Zhang, Jin}
}
@article {Simula.ND.237,
	title = {Secondary Spectrum Access Networks: Spatial Modeling and System Design},
	journal = {IEEE Vehicular Technology Magazine},
	volume = {4},
	number = {2},
	year = {2009},
	pages = {36-43},
	author = {Hong, X. and Wang, C. and Chen, H. and Zhang, Yan}
}
@article {Simula.ND.249,
	title = {Service Differentiation in OFDM-Based IEEE 802.16 Networks},
	journal = {EURASIP Journal on Wireless Communications and Networking},
	volume = {vol. 2009},
	number = {Article ID 635304, doi:10.1155/2009/635304.},
	year = {2009},
	publisher = {Springer},
	author = {Zhou, Y. and He, J. and Chen, K. and Liang, A. and Zhang, Yan}
}
@inproceedings {Simula.ND.259,
	title = {Spectrum Handoff in Cognitive Radio Networks: Opportunistic and Negotiated Situations},
	journal = {the IEEE International Conference on Communications (ICC), ICC 2009},
	year = {2009},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-3435-0},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@article {Simula.nd.455,
	title = {On Stability Regions in Opportunistic Scheduled Packet Access Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {59},
	number = {1},
	year = {2009},
	pages = {295-306},
	author = {Guo, H. and Hu, H. and Zhang, Yan and Chen, H.}
}
@inproceedings {Simula.ND.91,
	title = {An Analysis of K-Connectivity in Shadowing and Nakagami Fading Wireless Multi-Hop Networks},
	journal = {the IEEE 67th Vehicular Technology Conference (VTC2008-Spring)},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {9781424416448},
	author = {Zhang, L. and Soong, B. and Zhang, Yan and Ma, M. and Guan, Y.},
	editor = {IEEE, }
}
@article {Zhang.2006.13,
	title = {An Approximation and Its Applications in Wireless Networks Performance Analysis},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {8},
	number = {1},
	year = {2008},
	pages = {113-124},
	publisher = {John Wiley \& Sons, Ltd},
	author = {Zhang, Yan and Fujise, M.}
}
@inproceedings {Simula.ND.92,
	title = {Authentication Overhead in Wireless Networks},
	journal = {the IEEE International Conference on Communications (ICC), ICC 2008},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-2075-9},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@article {Zhang.2006.14,
	title = {Authentication Traffics Modeling and Analysis in Next Generation Wireless Networks},
	journal = {Wiley Wireless Communications and Mobile Computing},
	volume = {8},
	number = {5},
	year = {2008},
	pages = {615-625},
	author = {Zhang, Yan and Xiao, S. and Fujise, M.}
}
@inproceedings {Simula.ND.93,
	title = {Call Admission Control in OFDM Wireless Multimedia Networks},
	journal = {the IEEE International Conference on Communications (ICC), ICC 2008},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-2075-9},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.141,
	title = {Demystifying Spatial White Spaces Using Stochastic Geometry},
	journal = {International Conference on Communications, Circuits and Systems (ICCCAS 2008)},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-2063-6},
	author = {Hong, X. and Wang, C. and Thompson, J. and Zhang, Yan},
	editor = {IEEE, }
}
@article {Simula.ND.99,
	title = {Development of an Integrated Wireless Sensor Network Micro-Environment Monitoring System},
	journal = {ISA Transactions},
	volume = {47},
	number = {3},
	year = {2008},
	pages = {247-255},
	author = {Cao, X. and Chen, J. and Zhang, Yan and Sun, Y.}
}
@inproceedings {Simula.ND.94,
	title = {Dynamic Spectrum Access in Cognitive Radio Wireless Networks},
	journal = {the IEEE International Conference on Communications (ICC), ICC 2008},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-2075-9},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@article {Simula.ND.161,
	title = {Dynamic Spectrum Access in Heterogeneous Unlicensed Wireless Networks},
	journal = {International Journal of Autonomous and Adaptive Communications Systems},
	volume = {1},
	number = {1},
	year = {2008},
	pages = {148-163},
	author = {He, J. and Zhang, Yan and Kaleshi, D. and Munro, A. and McGeehan, J.}
}
@article {Simula.ND.56,
	title = {An Effective QoS Differentiation Scheme for Wireless Mesh Networks},
	journal = {IEEE Network},
	volume = {22},
	number = {1},
	year = {2008},
	month = {Jan./Feb.},
	pages = {66-73},
	author = {Hu, H. and Zhang, Yan and Chen, H.}
}
@inproceedings {Simula.ND.143,
	title = {Extended Iterative Flipping Algorithm for PAPR Reduction in OFDM Systems},
	journal = {International Conference on Communications and Networking in China (CHINACOM 2008)},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-2373-6},
	author = {Zhu, Xiaofei and Zhu, G. and Jiang, T. and Zhang, Yan},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.243,
	title = {Geographic Routing in Wireless Multimedia Sensor Networks},
	journal = {The 2nd International Conference on Future Generation Communication and Networking (FGCN 2008)},
	year = {2008},
	publisher = {IEEE Computer Society},
	type = {Conference},
	isbn = {978-0-7695-3431-2},
	author = {Shu, L. and Zhang, Yan and Yang, L. and Wang, Y. and Hauswirth, M.},
	editor = {IEEE, }
}
@article {Simula.ND.133,
	title = {A High-Throughput Random Access Protocol for Multiuser MIMO Systems},
	journal = {EURASIP Research Letters in Communications},
	volume = {2008},
	number = {730610},
	year = {2008},
	pages = {5},
	doi = {10.1155/2008/730610},
	author = {Guo, H. and Hu, H. and Zhang, Yan}
}
@inproceedings {Simula.ND.197,
	title = {Joint Admission and Power Control for Cognitive Radio Cellular Networks},
	journal = {the 11th IEEE International Conference on Communication Systems 2008 (ICCS 2008), invited paper},
	year = {2008},
	month = {November},
	pages = {1519-1523},
	publisher = {IEEE},
	type = {Conference},
	abstract = {In cognitive radio cellular networks (CogCell), the Secondary Users (SUs) can be admitted to the Base Station (BS) provided that the interference caused by SUs to the Primary Users (PUs) is no higher than the pre-defined threshold. In addition, different SUs may require different Quality of Service (QoS) and hence make different payment based on the provided QoS level. In this paper, we investigate the maximally achievable revenue obtained from SUs subjected to the interference constraints on PUs and QoS requirements of SUs. To solve the identified issue, we introduce the revenue efficiency factor and propose an efficient Joint Admission and Power Control scheme using a Minimal Revenue Efficiency Removal algorithm (JAPC-MRER). With comparison to the other two schemes JAPC-MSRA and JAPC-Random, our strategy is able to achieve much higher revenue with guaranteed interference requirements and QoS demands. In addition, the proposed scheme is evaluated with the effects of the key parameters, i.e. the number of PUs, the number of SUs and the interference threshold.},
	isbn = {978-1-4244-2423-8},
	doi = {10.1109/ICCS.2008.4737437},
	author = {Xiang, Jie and Zhang, Yan and Skeie, Tor},
	editor = {Gang Wei Lawren {Wong}}
}
@inproceedings {Simula.ND.245,
	title = {NetTopo: Beyond Simulator and Visualizer for Wireless Sensor Networks},
	journal = {The 2nd International Conference on Future Generation Communication and Networking (FGCN 2008)},
	year = {2008},
	publisher = {IEEE Computer Society},
	type = {Conference},
	isbn = {978-0-7695-3431-2},
	author = {Shu, L. and Wu, C. and Zhang, Yan and Chen, J. and Wang, L. and Hauswirth, M.},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.247,
	title = {A Novel Multi-Channel MAC Scheme for Vehicular Ad Hoc Networks},
	journal = {First International Conference on Wireless Access in Vehicular Environments (WAVE 2008)},
	year = {2008},
	publisher = {IEEE VTS},
	type = {Conference},
	isbn = {1424434483},
	author = {Wang, Q. and Fu, H. and Zhang, Yan},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.104,
	title = {Optimal Fault-Tolerant Broadcasting in Wireless Mesh Networks},
	journal = {International Conference on High Performance Switching and Routing (HPSR{\textquoteright}08)},
	year = {2008},
	month = {May},
	pages = {151-157},
	publisher = {IEEE press},
	type = {Conference},
	abstract = {Wireless Mesh Networks (WMNs) is an emerging communication paradigm to enable resilient, cost-efficient and reliable services for the future-generation wireless networks. In this paper, we study the broadcasting (one-to-all communication) in WMNs with known topology, i.e., where for each primitive the schedule of transmissions is precomputed in advance based on full knowledge about the size and the topology of the network. We show that broadcasting can complete in D+O({\l}og n) time units in the WMN with size n and diameter D. Furthermore, we explore the fault-tolerant broadcasting in WMN. We show an O(n)-time deterministic radio broadcasting schedule with large number of link failures. This is an optimal schedule in the sense that there exists a network topology in which the broadcasting cannot complete in less than {\O}mega(n) units of time.},
	isbn = {978-1-4244-1982-1},
	author = {Xin, Qin and Zhang, Yan},
	editor = {Song, Min and Yamanaka, Naoaki and Bianco, Andrea and Jin, Yaohui}
}
@inproceedings {Simula.ND.163,
	title = {Optimal Rate Routing in Wireless Sensor Networks With Guaranteed Lifetime},
	journal = {IEEE Global Communications Conference (IEEE GLOBECOM 2008)},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-2324-8},
	author = {Xu, W. and Chen, J. and Zhang, Yan and Xiao, Y. and Sun, Y.},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.123,
	title = {Optimal Spectrum Scheduling in Cognitive Wireless Mesh Networks},
	journal = {Proceedings of International Wireless Communications and Mobile Computing Conference 2008 (IWCMC{\textquoteright}08)},
	year = {2008},
	pages = {724-728},
	publisher = {IEEE press},
	type = {Conference},
	abstract = {In a Cognitive Wireless Mesh Network (CogMesh), each Cognitive Radio (CR) enabled mesh node can sense and opportunistically access the under-utilized spectrums in the primary system. Since the unoccupied spectrum is location-dependent and time-dependent, the available spectrums in each mesh node are different. With this spectrum heterogeneity, each node shall have the knowledge of spectrum, scheduling, and routing path of other nodes such that it cacommunicate with them with minimal cost and no collision. The problem may occur in a number of the situations, e.g. the routing table re-building and the unicast real-time applications. In this paper, we focus on the 2-hop spectrum scheduling, which will enable any pair of 2-hop neighborhood nodes know the spectrum, collision-free scheduling, and minimal-cost routing path. Two optimal strategies are proposed to address the spectrum scheduling: Optimal Deterministic Spectrum Scheduling (ODS) and Optimal Randomized Spectrum Scheduling (ORS). In the deterministic situation, with the scheme ODS, the 2-hop spectrum scheduling can be solved in polynomial time. In the randomized situation, with the scheme ORS, the 2-hop spectrum scheduling can be solved in polynomial time with high probability at least (1-\frac{1}{n}) where n denotes the network size. The simulation experiment is carried out to show the achievable performance of the proposed algorithms.},
	isbn = {978-1-4244-2202-9},
	author = {Xin, Qin and Zhang, Yan and Xiang, Jie},
	editor = {Chen, Hsiao-Hwa and Zhang, Xi and Guizani, Mohsen and Athanasios V. {Vasilakos}}
}
@article {Simula.ND.96,
	title = {Performance Improvement and Wavelength Reuse in Millimeter-Wave Radio-Over-Fiber Links Incorporating All-Fiber Optical Interleaver},
	journal = {Optics Communications},
	volume = {281},
	number = {9},
	year = {2008},
	pages = {2572-2581},
	author = {Wang, Q. and Luo, B. and Guo, Y. and Ong, C. and Zhang, Yan and Zhang, Yan and Soh, Y. and Miura, R.}
}
@article {Simula.ND.97,
	title = {QoS Differentiation for IEEE 802.16 WiMAX Mesh Networking},
	journal = {Mobile Networks and Applications},
	volume = {13},
	number = {1-2},
	year = {2008},
	pages = {19-37},
	author = {Zhang, Yan and Hu, H. and Chen, H.}
}
@inproceedings {Simula.ND.147,
	title = {QoS-Aware Channel Selection in Cognitive Radio Networks: a Game-Theoretic Approach},
	journal = {IEEE Global Communications Conference (GLOBECOM 2008)},
	year = {2008},
	pages = {1-7},
	publisher = {IEEE},
	type = {Conference},
	abstract = {Abstract-In a cognitive radio wireless network, each node can sense and opportunistically access the under-utilized spectrums in the primary system. Since the unoccupied spectrum is locationdependent and time-dependent, the available spectrums in each node are different.With this spectrum heterogeneity and different Quality-of-Service (QoS) requirement, different node may have different preference in using a particular channel to communicate with its neighboring nodes. In this paper, we formulate this channel selection problem using a cooperative game theoretical approach such that the QoS requirement of each node is guaranteed and the total throughput is maximized. To further improve the performance, a learning negotiation mechanism is introduced. The key motivation is to derive new mixed strategies of the nodes with the reference to the historical profiles of all selected strategies in the past. Simulation results are presented to show the fast convergence of the game, the high efficiency of the learning mechanism, and the effect of mobility.},
	isbn = {978-1-4244-2324-8},
	doi = {10.1109/GLOCOM.2008.ECP.934},
	author = {Hai Ngoc {Pham} and Xiang, Jie and Zhang, Yan and Skeie, Tor},
	editor = {Richard W. {Miller}}
}
@article {Simula.ND.55,
	title = {Queueing Analysis for OFDM Subcarrier Allocation in Broadband Wireless Multiservice Networks},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {7},
	number = {10},
	year = {2008},
	month = {Oct.},
	pages = {3951-3961},
	author = {Zhang, Yan and Xiao, Y. and Chen, H.}
}
@inproceedings {Simula.ND.145,
	title = {Revenue-Based Admission Control for Cognitive Radio Cellular Systems},
	journal = {2008 International Workshop on Cognitive Networks and Communications (COGCOM 2008), in conjunction with CHINACOM 2008},
	year = {2008},
	publisher = {IEEE VTS},
	type = {Workshop},
	isbn = {978-1-4244-2373-6},
	author = {Xie, Lang and Xiang, Jie and Zhang, Yan},
	editor = {IEEE, }
}
@article {Simula.ND.137,
	title = {Transmitting and Gathering Streaming Data in Wireless Multimedia Sensor Networks Within Expected Network Lifetime},
	journal = {Mobile Networks and Applications},
	volume = {13},
	number = {3-4},
	year = {2008},
	pages = {306-322},
	author = {Shu, L. and Zhang, Yan and Zhou, Z. and Hauswirth, M. and Yu, Z. and Hynes, G.}
}
@inproceedings {Simula.ND.95,
	title = {Utility-Based Weighted Prioritization in Heterogeneous Wireless Networks},
	journal = {the IEEE International Conference on Circuits \& Systems for Communications (ICCSC), ICCSC 2008},
	year = {2008},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-1708-7},
	author = {Zhang, Yan and Soong, B. and Zhang, L.},
	editor = {IEEE, }
}
@article {Simula.ND.23,
	title = {Adaptive Location Update Area Design for Wireless Cellular Networks Under 2D Markov Walk Model},
	journal = {Computer Communications},
	volume = {30},
	number = {9},
	year = {2007},
	pages = {2060-2069},
	author = {Zhang, Jin and Zhang, Yan and Wang, L. and Chen, J.}
}
@inproceedings {Zhang.2007.2,
	title = {Call Admission Control in Wireless Networks Over Rayleigh Fading Channel},
	journal = {IEEE Wireless Communications and Networking Conference (WCNC), WCNC{\textquoteright}2007},
	year = {2007},
	pages = {3030-3034},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0659-5},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@article {Zhang.2006.11,
	title = {Call Completion in Wireless Network Over Lossy Link},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {56},
	number = {2},
	year = {2007},
	pages = {929-941},
	author = {Zhang, Yan and Ma, M. and Fujise, M.}
}
@inproceedings {Chen.2007.1,
	title = {Cross-Correlation Analysis of Generalized Distributed Antenna Systems With Cooperative Diversity},
	journal = {the 65th IEEE Vehicular Technology Conference (VTC2007-Spring)},
	year = {2007},
	pages = {309-313},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0266-2},
	author = {Chen, Y. and Yuen, C. and Zhang, Yan and Zhang, Z.},
	editor = {IEEE, }
}
@article {Zhou.2006.1,
	title = {Design of Millimeter-Wave Fiber-Wireless Downlink With Remote Local-Oscillator Delivery by Using Dual-Electrode Mach-Zehnder Modulators Configured for Optical Single-Sideband Modulations},
	journal = {Optics Communications},
	volume = {269},
	number = {1},
	year = {2007},
	pages = {69-75},
	author = {Zhang, Jin and Sharma, A.B and Zhang, Yan and Fujise, M.}
}
@book {Simula.ND.2,
	title = {Distributed Antenna Systems: Open Architecture for Future Wireless Communications},
	year = {2007},
	month = {May},
	publisher = {Auerbach Publications},
	edition = {first},
	address = {New York},
	isbn = {1420042882},
	author = {Hu, H. and Zhang, Yan and Luo, J.}
}
@inbook {Simula.ND.3,
	title = {Diversity and Multiplexing for DAS: Channel Modeling Perspective},
	booktitle = {Distributed Antenna Systems: Open Architecture for Future Wireless Communications},
	year = {2007},
	month = {May},
	pages = {1-30},
	publisher = {Auerbach Publications},
	organization = {Auerbach Publications},
	chapter = {1},
	address = {New York},
	isbn = {1420042882},
	author = {Chen, Y. and Zhang, Yan and Yuen, C. and Zhang, Z.},
	editor = {Zhang H. {Hu} and Luo, J.}
}
@inproceedings {Chen.2007.2,
	title = {Diversity Gains of Generalized Distributed Antenna Systems With Cooperative Users},
	journal = {IEEE Wireless Communications and Networking Conference (WCNC), WCNC{\textquoteright}2007},
	year = {2007},
	pages = {798-803},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0659-5},
	author = {Chen, Y. and Yuen, C. and Zhang, Yan and Zhang, Z.},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.14,
	title = {Energy and QoS Aware Packet Forwarding in Wireless Sensor Networks},
	journal = {the IEEE International Conference on Communications (ICC), ICC 2007},
	year = {2007},
	pages = {3277-3282},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0353-7},
	author = {Yu, Rong and Zhang, Yan and Sun, Z. and Mei, S.},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.5,
	title = {Handoff Probability in Wireless Networks Over Rayleigh Fading Channel: a Cross-Layer Approach},
	journal = {the IEEE International Conference on Communications (ICC), ICC{\textquoteright}2007},
	year = {2007},
	month = {June},
	pages = {5660-5664},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0353-7},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@article {Zhang.2006.12,
	title = {Location Management Congestion Problem in Wireless Networks},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {56},
	number = {2},
	year = {2007},
	pages = {942-954},
	author = {Zhang, Yan and Fujise, M.}
}
@book {Simula.ND.47,
	title = {Mobile WiMAX: Toward Broadband Wireless Metropolitan Area Networks},
	year = {2007},
	publisher = {Auerbach Publications},
	edition = {first},
	address = {New York},
	isbn = {9780849326240},
	author = {Zhang, Yan and Chen, H.}
}
@inproceedings {Simula.ND.67,
	title = {A New Adaptive Energy Management Scheme in IEEE 802.16e Mobile WiMAX},
	journal = {Norwegian Informatics Conference 2007 (NIK 2007)},
	year = {2007},
	pages = {111-114},
	publisher = {Tapir Akademisk Forlag},
	type = {Conference},
	isbn = {978-82-519-2272-2},
	author = {Zhang, Yan and Xiang, Jie},
	editor = {Frode Eika {Sandnes}}
}
@inproceedings {Simula.ND.10,
	title = {Performance Evaluation of RFID Anti-Collision Algorithm With FPGA Implementation},
	journal = {the Second IEEE International Symposium on Pervasive Computing and Ad Hoc Communications (PCAC-07)},
	year = {2007},
	publisher = {IEEE Computer Society Press},
	type = {Conference},
	isbn = {0-7695-2847-3},
	author = {Ning, H. and Cong, Y. and Xu, Z. and Hong, T. and Zhao, J. and Zhang, Yan},
	editor = {IEEE, }
}
@inproceedings {Zhang.2007.3,
	title = {Performance Modeling of Energy Management Mechanism in IEEE 802.16e Mobile WiMAX},
	journal = {IEEE Wireless Communications and Networking Conference (WCNC), WCNC{\textquoteright}2007},
	year = {2007},
	pages = {3205-3209},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0659-5},
	author = {Zhang, Yan},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.12,
	title = {Quantitative Analysis of Location Management and QoS in Wireless Mobile Networks},
	journal = {the IEEE 21st International Conference on Advanced Information Networking and Applications (AINA-07)},
	year = {2007},
	pages = {573-579},
	publisher = {IEEE Computer Society Press},
	type = {Conference},
	isbn = {0-7695-2846-5},
	author = {Zhang, Yan and Laurence T. {Yang} and Ma, J. and Zhang, Jin and Xiao, S.},
	editor = {IEEE, }
}
@inproceedings {Simula.ND.38,
	title = {Queueing Analysis of OFDM Subcarrier Allocation in Wireless Multimedia Networks},
	journal = {IEEE International Symposium on Wireless Communication Systems 2007 (IEEE ISWCS{\textquoteright}07)},
	year = {2007},
	pages = {81-85},
	publisher = {IEEE},
	type = {Conference},
	isbn = {978-1-4244-0979-2},
	author = {Zhang, Yan and Chen, Y.},
	editor = {IEEE, }
}
@inproceedings {Zhang.2007.1,
	title = {A Simple and Effective QoS Differentiation Scheme in IEEE 802.16 WiMAX Mesh Networking},
	journal = {IEEE Wireless Communications and Networking Conference (WCNC), WCNC{\textquoteright}2007},
	year = {2007},
	pages = {3216-3220},
	publisher = {IEEE},
	type = {Conference},
	isbn = {1-4244-0659-5},
	author = {Zhang, Yan and Zhang, Jin and Li, W.},
	editor = {IEEE, }
}
@inbook {Zhang.2006.3,
	title = {Dynamic Channel Allocation Schemes in GPRS Networks},
	booktitle = {Adaptation Techniques in Wireless Multimedia Networks},
	series = {Wireless Networks and Mobile Computing},
	year = {2006},
	publisher = {Nova Science Publishers},
	organization = {Nova Science Publishers},
	chapter = {14},
	address = {New York},
	isbn = {1-59454-883-8},
	author = {Zhang, Yan and Soong, B. and Jiang, Y.},
	editor = {Li, W. and Xiao, Y.}
}
@article {Zhang.2006.5,
	title = {A Dynamic Channel Assignment Scheme for Voice/Data Integration in GPRS Networks},
	journal = {Computer Communications},
	volume = {29},
	number = {8},
	year = {2006},
	month = {May},
	pages = {1163-1173},
	author = {Zhang, Yan and Soong, B. and Ma, M.}
}
@article {Zhang.2006.9,
	title = {Energy Management in the IEEE 802.16e MAC},
	journal = {IEEE Communications Letters},
	volume = {10},
	number = {4},
	year = {2006},
	month = {Apr.},
	pages = {311-313},
	author = {Zhang, Yan and Fujise, M.}
}
@inbook {Zhang.2006.16,
	title = {IEEE 802.16 WiMAX Mesh Networking},
	booktitle = {Wireless Mesh Networking: Architectures, Protocols and Standards},
	year = {2006},
	pages = {425-466},
	publisher = {Auerbach Publications},
	organization = {Auerbach Publications},
	chapter = {13},
	address = {New York},
	isbn = {0849373999},
	author = {Zhang, Yan and Tan, K.S and Kong, P.Y and Zhang, Jin and Fujise, M.},
	editor = {Luo Y. {ZHANG} and Hu, H.}
}
@article {Zhang.2006.8,
	title = {An Improvement for Authentication Protocol in Third-Generation Wireless Networks},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {5},
	number = {9},
	year = {2006},
	month = {Sept.},
	pages = {2348-2352},
	author = {Zhang, Yan and Fujise, M.}
}
@inbook {Zheng.2006.2,
	title = {Medium Access Control in Wireless Ad Hoc Networks},
	booktitle = {Resource, Mobility and Security Management in Wireless Networks and Mobile Communications},
	year = {2006},
	publisher = {Auerbach Publications},
	organization = {Auerbach Publications},
	address = {New York},
	isbn = {0849380367},
	author = {Zhang, Jin and Ma, M. and Zhang, Yan and Fujise, M.},
	editor = {Zhang, Yan and Hu, H. and Fujise, M.}
}
@article {Zhang.2006.6,
	title = {Modeling Location Management in Wireless Networks With Generally Distributed Parameters},
	journal = {Computer Communications},
	volume = {29},
	number = {12},
	year = {2006},
	pages = {2386-2395},
	author = {Zhang, Yan and Zhang, Jin and Zhang, L. and Chen, Y. and Ma, M.}
}
@article {Zhang.2006.10,
	title = {Performance Analysis of Wireless Networks Over Rayleigh Fading Channel},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {55},
	number = {5},
	year = {2006},
	month = {Sept.},
	pages = {1621-1632},
	author = {Zhang, Yan and Fujise, M.}
}
@article {Zhang.2006.7,
	title = {Performance of Mobile Networks With Wireless Channel Unreliability and Resource Insufficiency},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {5},
	number = {5},
	year = {2006},
	month = {May},
	pages = {990-995},
	author = {Zhang, Yan and Soong, B.}
}
@book {Zhang.2006.1,
	title = {Resource, Mobility, and Security Management in Wireless Networks and Mobile Communications},
	year = {2006},
	month = {Nov.},
	publisher = {Auerbach Publications},
	edition = {first},
	address = {New York},
	isbn = {0849380367},
	author = {Zhang, Yan and Hu, H. and Fujise, M.}
}
@article {Zhang.2006.4,
	title = {Security Management in the Next Generation Wireless Networks},
	journal = {International Journal of Network Security},
	volume = {3},
	number = {1},
	year = {2006},
	month = {July},
	pages = {1-7},
	author = {Zhang, Yan and Fujise, M.}
}
@article {Zheng.2006.1,
	title = {Virtual Guard Channel for Handoff Calls in Integrated Voice/Data Wireless Networks},
	journal = {IEEE Communications Letters},
	volume = {10},
	number = {4},
	year = {2006},
	month = {Apr.},
	pages = {263-265},
	author = {Zhang, Jin and Zhang, Yan and Regentova, E.}
}
@book {Zhang.2006.2,
	title = {Wireless Mesh Networking: Architectures, Protocols and Standards},
	year = {2006},
	month = {Dec.},
	publisher = {Auerbach Publications},
	edition = {first},
	address = {New York},
	isbn = {0849373999},
	author = {Zhang, Yan and Luo, J. and Hu, H.}
}
@inbook {Zhang.2006.15,
	title = {Wireless Networks Tele-Traffic Modeling Over Lossy Link},
	booktitle = {Resource, Mobility and Security Management in Wireless Networks and Mobile Communications},
	year = {2006},
	publisher = {Auerbach Publications},
	organization = {Auerbach Publications},
	address = {New York},
	isbn = {0849380367},
	author = {Zhang, Yan and Li, W. and Xiao, Y. and Xiao, S. and Fujise, M.},
	editor = {Zhang, Yan and Hu, H. and Fujise, M.}
}
@article {Xiao.2005.1,
	title = {Bandwidth-Enhancing Ultralow-Profile Compact Patch Antenna},
	journal = {IEEE Transactions on Antennas and Propagation},
	volume = {53},
	number = {11},
	year = {2005},
	month = {Nov.},
	pages = {3443-3447},
	author = {Xiao, S. and Wang, B. and Shao, W. and Zhang, Yan}
}
@article {Zhang.2005.1,
	title = {The Effect of Unreliable Wireless Channel on the Call Performance in Mobile Network},
	journal = {IEEE Transactions on Wireless Communications},
	volume = {4},
	number = {2},
	year = {2005},
	month = {Mar.},
	pages = {653-661},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2005.2,
	title = {Handoff Dwell Time Distribution Effect on Mobile Network Performance},
	journal = {IEEE Transactions on Vehicular Technology},
	volume = {54},
	number = {4},
	year = {2005},
	month = {July},
	pages = {1500-1508},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2005.3,
	title = {Performance Evaluation of Queue With Unreliable Wireless Channel},
	journal = {IEE Proceedings Communications},
	volume = {152},
	number = {6},
	year = {2005},
	month = {Dec.},
	pages = {1028-1030},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2004.4,
	title = {Channel Holding Time in Hierarchical Cellular Systems},
	journal = {IEEE Communications Letters},
	volume = {8},
	number = {10},
	year = {2004},
	month = {Oct.},
	pages = {614-616},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2004.3,
	title = {The Effect of Handoff Dwell Time on the Mobile Network Performance},
	journal = {Wireless Personal Communications},
	volume = {31},
	number = {3-4},
	year = {2004},
	month = {Dec.},
	pages = {221-234},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2004.5,
	title = {Handoff Counting in Hierarchical Cellular System With Overflow Scheme},
	journal = {Computer Networks},
	volume = {46},
	number = {4},
	year = {2004},
	month = {Nov.},
	pages = {541-554},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2004.2,
	title = {Performance Evaluation of GSM/GPRS Networks With Channel Re-Allocation Scheme},
	journal = {IEEE Communications Letters},
	volume = {8},
	number = {5},
	year = {2004},
	month = {May},
	pages = {280-282},
	author = {Zhang, Yan and Soong, B.}
}
@article {Zhang.2003.1,
	title = {Approximation Approach on Performance Evaluation for Guard Channel Scheme},
	journal = {IEE Electronics Letters},
	volume = {39},
	number = {5},
	year = {2003},
	month = {Mar.},
	pages = {465-467},
	author = {Zhang, Yan and Soong, B. and Ma, M.}
}
