@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 {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 {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 {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}
}
@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 {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}
}
@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}
}
