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Seminar Announcement December 24, Saturday, 15:00-17:00, Room: A302, WNLO Title: Quality-of-Experience (QoE) and Power Efficiency Tradeoff for Fog Computing.

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Presentation on theme: "Seminar Announcement December 24, Saturday, 15:00-17:00, Room: A302, WNLO Title: Quality-of-Experience (QoE) and Power Efficiency Tradeoff for Fog Computing."— Presentation transcript:

1 Seminar Announcement December 24, Saturday, 15:00-17:00, Room: A302, WNLO Title: Quality-of-Experience (QoE) and Power Efficiency Tradeoff for Fog Computing Networks Dr . Yong Xiao (肖泳) Research Assistant Professor University of Arizona Abstract Fog computing is a visualized network architecture that uses one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of storage, communication, and control, configuration, measurement, and management. It can offload the computation workload to the cloud data centers, reduce the transmission latency, and ease traffic congestion of the Internet. It also enables many new services and applications that cannot fit well in the traditional cloud computing architecture. In this talk, I will first briefly introduce the recent developments in the mobile cloud and fog computing. I will then introduce two important performance metrics for fog computing networks: quality-of-experience (QoE) and power efficiency. A fundamental tradeoff between QoE and power efficiency will then be discussed. Motivated by the observation that the users’ QoE can be further improved if the workload offloading process of each fog node can be helped by others, I also talk about a fog computing framework with fog node cooperation. The QoE and power efficiency tradeoff under cooperative fog computing will be discussed. A novel distributed optimization framework based on distributed alternating direction method of multipliers (ADMM) via variable splitting to achieve the optimal tradeoff solution will be introduced. Finally, a fog computing platform supported by a wireless infrastructure as a case study to verify the performance of the proposed framework. Biography Yong Xiao is a Research Assistant Professor in the Department of Electrical and Computer Engineering at the University of Arizona. He is also the center manager of the NSF BWAC Center at the University of Arizona. Previously, he worked as Postdoc Research Fellow at Trinity College Dublin, Massachusetts Institute of Technology, and University of Houston. His research interests include game theory, machine learning, distributed optimization, economic modeling and their applications in cyber-physical systems, green communication networks, wireless communication networks, internet of things (IoT), smart grid and energy harvesting networks, wireless power transfer, and mobile cloud computing. He is an IEEE Senior Member.


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