@inproceedings { ISCC2023,
	title = {Proactive Resource Orchestration Framework for Cloud/Fog Platform},
	journal = {Proceedings of the 28th IEEE Symposium on Computers and Communications (ISCC)},
	year = {2023},
	publisher = { IEEE},
	address = {Tunis/Tunisia},
	abstract = {Cloud computing makes complex computing an off-premise activity by offering software- and hardware-based services using standard security protocols over the Internet. It has been seen that the cloud is not ideal for latency-sensitive applications. Thanks to the current growth of network communication and infrastructure, fog adds a computing resource delegation layer between the user and the cloud. Fog aims to improve latency-sensitive applications support. Here, we propose one unified, proactive resource orchestration framework from a cloud/fog service provider perspective. The framework consists of a predictor and a resource allocator module. Users subscribe to these resources to execute their applications. The framework does not require application-specific information and is modular, meaning a service provider can customise each module. We have presented the framework prototype by showing each module{\textquoteright}s simulated performance results using the parameters of our cloud/fog research test bed.},
	keywords = {Cloud, Fog, Orchestration, Prediction, Resource Allocation},
	author = {Mazumdar, Somnath and Dreibholz, Thomas}
}
@inproceedings { SEAA2023,
	title = {Towards A Data Privacy-Aware Execution Zone Creation on Cloud/Fog Platform},
	journal = {Proceedings of the 49th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA)},
	year = {2023},
	publisher = { IEEE},
	address = {Durr{\"e}s/Albania},
	abstract = {Cloud computing is now a {\textquoteleft}go-to{\textquoteright} platform for running various types of application. A wide spectrum of users needing software and hardware resources have embraced the cloud. Following the cloud business model, one is either a cloud-based service provider or a cloud service (hardware and software) user. There is a continuous evolution in the cloud ecosystem to support the ever-changing features of user applications. The cloud ecosystem has added a new resource delegation model to accommodate such new requirements. This new resource delegation model is known as fog. Both cloud and fog platforms employ complex hardware and software to provide better run-time support for applications. This paper presents a message-based privacy-aware application execution zone management framework for the cloud/fog platform. The framework aims to create a static execution zone based on the performance of the user application and the data privacy requirements. It also enables the user to set the resource termination conditions. Here, we have prototyped the proposed framework and showed how the proposed approach works with message structure and experiments with the P4 switch. We also present how the prototype could be implemented on a cloud/fog platform.},
	keywords = {Cloud, Data, Fog, Message, Privacy, resource management},
	author = {Mazumdar, Somnath and Dreibholz, Thomas}
}
@article { IoT2023,
	title = {Towards a Lightweight Task Scheduling Framework for Cloud and Edge Platform},
	journal = {Internet of Things; Engineering Cyber Physical Human Systems},
	year = {2023},
	publisher = {Elsevier},
	abstract = {Mobile devices are becoming ubiquitous in our daily lives, but they have limited computational capacity. Thanks to the advancement in the network infrastructure, task offloading from resource-constrained devices to the near edge and the cloud becomes possible and advantageous. Complete task offloading is now possible to almost limitless computing resources of public cloud platforms. Generally, the edge computing resources support latency-sensitive applications with limited computing resources, while the cloud supports latency-tolerant applications. This paper proposes one lightweight task-scheduling framework from cloud service provider perspective, for applications using both cloud and edge platforms. Here, the challenge is using edge and cloud resources efficiently when necessary. Such decisions have to be made quickly, with a small management overhead. Our framework aims at solving two research questions. They are: i) How to distribute tasks to the edge resource pools and multi-clouds? ii) How to manage these resource pools effectively with low overheads? To answer these two questions, we examine the performance of our proposed framework based on Reliable Server Pooling (RSerPool). We have shown via simulations that RSerPool, with the correct usage and configuration of pool member selection policies, can accomplish the cloud/edge setup resource selection task with a small overhead.},
	keywords = {Cloud computing, Edge Computing, Reliable Server Pooling (RSerPool), Resource Pools, Task Scheduling},
	author = {Dreibholz, Thomas and Mazumdar, Somnath}
}
@inproceedings { CNSM2022,
	title = {Find Out: How Do Your Data Packets Travel?},
	journal = {Proceedings of the 18th IEEE International Conference on Network and Service Management (CNSM)},
	year = {2022},
	month = {11/2022},
	publisher = { IEEE},
	address = {Thessaloniki, Greece},
	abstract = {In today{\textquoteright}s communication-centric world, users generate and exchange a huge amount of data. The Internet helps user data to travel from one part of the world to another via a complex setting of network systems. These systems are intelligent, heterogeneous, and non-transparent to users. In this paper, we present an extensive trace-driven study of user data traffic covering five years of observations, six large ISPs, 21 different autonomous systems, and a total of 13 countries. The aim of this work is to make users aware about how their data travels in the Internet, as the data traffic path is majorly influenced by the interests of ISPs. We showed that shortest land distance between the two countries does not impact data path selection, while data traffic prefers to travel even though country do not share land borders.},
	keywords = {connectivity, Data, Internet, Packets, Routing, Traffic Paths},
	isbn = {978-3-903176-51-5},
	author = {Dreibholz, Thomas and Mazumdar, Somnath}
}
@inproceedings { M2EC2022,
	title = {Load Distribution for Mobile Edge Computing with Reliable Server Pooling},
	journal = {Proceedings of the 4th International Workshop on Recent Advances for Multi-Clouds and Mobile Edge Computing~(M2EC) in conjunction with the 36th International Conference on Advanced Information Networking and Applications~(AINA)},
	year = {2022},
	publisher = { Springer},
	address = {Sydney, New South Wales/Australia},
	abstract = {Energy-efficient computing model is a popular choice for high performance as well as throughput oriented computing ecosystems. Mobile (computing) devices are becoming increasingly ubiquitous to our computing domain, but with limited resources (true both for computation as well as for energy). Hence, workload offloading from resource-constrained mobile devices to the Edge and maybe (later) to the cloud become necessary as well as useful. Thanks to the persistent technical breakthroughs in global wireless standards (or in mobile networks) together with the almost limitless amount of resources in public cloud platforms, workload offloading is possible and cheaper. In such scenarios, Mobile Edge Computing (MEC) resources could be provisioned in proximity to the users for supporting latency-sensitive applications. Here, two relevant problems could be: i) How to distribute workload to the resource pools of MEC as well as public (multi-)clouds? ii) How to manage such resource pools effectively? To answer these problems in this paper, we examine the performance of our proposed approach using the Reliable Server Pooling (RSerPool) framework in more detail. We also have outlined the resource pool management policies to effectively use RSerPool for workload offloading from mobile devices into the cloud/MEC ecosystem.},
	keywords = {Cloud computing, Load Distribution, Mobile Edge Computing (MEC), Multi-Cloud Computing, Reliable Server Pooling (RSerPool), Serverless Computing},
	author = {Dreibholz, Thomas and Mazumdar, Somnath}
}
@article { CommMag2022,
	title = {Secure Embedded Living: Towards a Self-contained User Data Preserving Framework},
	journal = {IEEE Communications Magazine},
	volume = {60},
	year = {2022},
	month = {11/2022},
	pages = {74{\textendash}80},
	publisher = { IEEE},
	abstract = {Smart living represents the hardware-software co-inhabiting with humans for better living standards and improved well-being. Here, hardware monitors human activities (by collecting data) specific to a context. Such data can be processed to offer context-specific valuable insights. Such insights can be used for optimising the well-being, living experience and energy cost of smart homes. This paper proposes a Secure Embedded Living Framework~(SELF) that enforces a privacy-preserving data control mechanism by integrating multiple technologies, such as Internet-of-thing, cloud/fog platform, machine learning and blockchain. The primary aim of the SELF is to allow the user to retain more control of its data.},
	keywords = {blockchain, Cloud, Data, IoTs, Security, User},
	issn = {0163-6804},
	doi = {10.1109/MCOM.001.2200165},
	author = {Mazumdar, Somnath and Dreibholz, Thomas}
}
@inproceedings { PDCAT2022,
	title = {Towards a Blockchain and Fog-Based Proactive Data Distribution Framework for ICN},
	journal = {Proceedings of the International Conference on Parallel and Distributed Computing, Applications and Technologies~(PDCAT)},
	year = {2022},
	address = {Sendai/Japan},
	abstract = {Most of today{\textquoteright}s IP traffic is cloud traffic. Due to a vast, complex and non-transparent Internet infrastructure, securely accessing and delegating data is not a trivial task. Existing technologies of Information-Centric Networking (ICN) make content distribution and access easy while primarily relying on the existing cloud-based security features. The primary aim of ICN is to make data independent of its storage location and application. ICN builds upon traditional distributed computing, which means ICN platforms also can suffer from similar data security issues as distributed computing platforms. We present our ongoing work to develop a secure, proactive data distribution framework. The framework answers the research question, i.e., How to extend online data protection with a secure data distribution model for the ICN platform? Our framework adds a data protection layer over the content distribution network, using blockchain and relying on the fog to distribute the contents with low latency. Our framework is different from the existing works in multiple aspects, such as i) data are primarily distributed from the fog nodes, ii) blockchain is used to protect data and iii) blockchain allows statistical and other information sharing among stakeholders (such as content creators) following access rights. Sharing statistics about content distribution activity can bring transparency and trustworthiness among the stakeholders, including the subscribers, into the ICN platforms. We showed such a framework is possible by presenting initial performance results and our reflections while implementing it on a cloud/fog research testbed.},
	keywords = {blockchain, Data, Distribution, Fog, ICN, Protection},
	author = {Mazumdar, Somnath and Dreibholz, Thomas}
}
@inproceedings { HPCC2022,
	title = {Towards a Privacy Preserving Data Flow Control via Packet Header Marking},
	journal = {Proceedings of the 24th International Conference on High Performance Computing, Data, and Analytics~(HPCC)},
	year = {2022},
	publisher = {IEEE},
	address = {Chengdu, Sichuan/People{\textquoteright}s Republic of China},
	abstract = {{Computing infrastructure is becoming ubiquitous thanks to the advancement in computing and the network domain. Reliable network communication is essential to offer good quality services, but it is not trivial. There are privacy concerns. Metadata may leak user information even if traffic is encrypted. Some countries have data privacy preserving-related regulations, but end-users cannot control through which path, networks, and hardware their data packets should travel. Even worse, the user cannot declare their privacy preferences. This paper presents an approach to tackle such privacy issues through data privacy-aware routing. The user can specify their preferences for packet routing using marking and filtering. Routing can work according to such specifications. It is implemented by P4, allowing a vendor-independent realisation with standard off-the-shelf hardware and open-source software components. We presented the initial experimental results of a proof-of-concept run on a unified cloud/fog research testbed.}},
	keywords = {Cloud, Data, Fog, P4, Packets, Privacy, Routing},
	author = {Mazumdar, Somnath and Dreibholz, Thomas}
}
@inproceedings { LCN2021-RSerPool-Demo,
	title = {A Demo of Workload Offloading in Mobile Edge Computing Using the Reliable Server Pooling Framework},
	journal = {Proceedings of the 46th IEEE Conference on Local Computer Networks~(LCN)},
	year = {2021},
	month = {10/2021},
	publisher = {IEEE Computer Society},
	address = {Edmonton, Alberta, Canada},
	abstract = {Mobile Edge Computing (MEC) places cloud resources nearby the user, to provide support for latency-sensitive applications. Offloading workload from resource-constrained mobile devices (such as smartphones) into the cloud ecosystem is becoming increasingly popular. In this demonstration, we show how to deploy a mobile network (with OpenAirInterface and Open Source MANO), as well as to adapt the Reliable Server Pooling (RSerPool) framework to efficiently manage MEC as well as multi-cloud resources to run an interactive demo application.},
	keywords = {Demonstration, Evolved Packet Core (EPC), Mobile Edge Computing (MEC), Multi-Cloud Computing, Network Function Virtualisation (NFV), Reliable Server Pooling (RSerPool)},
	url = {https://www.ieeelcn.org/lcn46demos/Demo_4_1570754367.pdf},
	author = {Dreibholz, Thomas and Mazumdar, Somnath}
}
@inproceedings { M2EC2021,
	title = {Reliable Server Pooling Based Workload Offloading with Mobile Edge Computing: A Proof-of-Concept},
	journal = {Advanced Information Networking and Applications (AINA 2021)},
	year = {2021},
	pages = {582-593},
	publisher = { Springer},
	abstract = {In recent times, mobile broadband devices have become almost ubiquitous. However, battery-powered devices (such as smartphones), have limitations on energy consumption, computation power and storage space. Cloud computing, and in particular with the upcoming 5G networks, Mobile Edge Computing (MEC) can provide compute and storage services at the vicinity of the user (with a low communication latency). However, the complexity lies in how to simply and efficiently realise MEC services, with the auxiliary public (multi-)cloud resources? In this paper, we propose a proof-of-concept of using Reliable Server Pooling (RSerPool) as a light-weight layer of managing resource pools and handling application sessions with these pools. Our approach is simple, efficient, has low overhead and is available as open-source. Here, we demonstrate the usefulness of our approach by measuring in a test setup, with a 4G testbed connected to MEC and public multi-cloud resources.},
	keywords = {5G, Evolved Packet Core (EPC), Mobile Edge Computing (MEC), Multi-Cloud Computing, Network Function Virtualisation (NFV), Reliable Server Pooling (RSerPool)},
	author = {Dreibholz, Thomas and Mazumdar, Somnath}
}
@inproceedings { PDP2019,
	title = {Mobile Edge as Part of the Multi-Cloud Ecosystem: A Performance Study},
	journal = {Proceedings of the 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing~(PDP)},
	year = {2019},
	month = {02/2019},
	pages = {59-66},
	publisher = {IEEE Computer Society},
	address = {Pavia, Lombardia/Italy},
	abstract = {Cloud computing has revolutionized the way of application usage and deployment: applications run cost-effectively in remote data centers. With the increasing need for mobility and micro-services, particularly with the upcoming 5G mobile broadband networks, there is also a strong demand for mobile edge computing (MEC): applications run in small cloud systems in close proximity to the user, in order to minimize latencies. Both cloud and MEC have their advantages and disadvantages. Combining the two approaches in a unified multi-cloud, consisting of both traditional cloud services provisioned over heterogeneous cloud platforms and MEC systems, has the potential of obtaining the best out of both worlds. However, a comprehensive study is needed to evaluate the performance gains and the overheads involved for real-world cloud applications. In this paper, we introduce a baseline performance evaluation in order to identify the fallacies and pitfalls of combining multiple cloud systems and MEC into a unified MEC-multi-cloud platform. For this purpose, we analyze the basic, application-independent performance metrics of average round-trip time (RTT) and average application payload throughput in a setup consisting of two private and one public cloud systems. This baseline performance analysis confirms the feasibility of MEC-multi-cloud, and provides guidelines for designing an autonomic resource provisioning solutions, in terms of an extension proposed to our existing Melodic middleware platform for multi-cloud applications.},
	keywords = {Cloud computing, latency, Mobile edge computing, Multi-Cloud, Performance},
	isbn = {978-1-7281-1644-0},
	doi = {10.1109/PDP.2019.00017},
	author = {Dreibholz, Thomas and Mazumdar, Somnath and Zahid, Feroz and Taherkordi, Amirhosein and Ernst Gunnar {Gran}}
}
