主题：Efficient and Low-Complexity Wireless Scheduling

           for Time-Sensitive Applications

时间：2月24日 上午9:30—10:30

地点：信电大楼215会议室

报告人：李宾博士

报告摘要（Abstract）：

With the fast growing deployment of smart mobile devices and increasingly predominant multimedia applications, the future wireless networks must provide high-quality services. This necessitates the design of efficient and low-complexity algorithms with various key characteristics: high throughput, fast convergence, low delay, regular service, and low energy consumption. In this talk, I will first briefly overview my dissertation research addressing these key aspects of the wireless scheduling design. Then, I will talk in more detail about my recent work on regular scheduling that is motivated by the stringent requirements of multimedia applications. Noting the difficulty in directly analyzing the service regularity, I introduce a new quantity, namely the time-since-last-service, whose evolution is markedly different from that of a traditional queue. By combining it with the queue-length in the weight, I propose a parametric class of maximum-weight type scheduling policies. I show that this policy is not only throughput-optimal but also provides regular service guarantees. Moreover, by carefully selecting its design parameter, the proposed algorithm can minimize the total mean queue-length to achieve mean delay optimality under heavily-loaded conditions while also enjoying the service regularity. To the best of our knowledge, this is the first work that rigorously studies the service regularity of the scheduling policies, which is an important metric for real-time applications.

This work has already developed a methodology to study the system dynamics beyond the traditional queue, which enables the incorporation of much sharper quality-of-service requirements than were possible before. It opens an interesting and new avenue to the performance analysis and optimization of the second or higher order metrics of general stochastic networks, including smart power grids and cloud computing.

报告人简介（Short Biography）：

Bin Li is currently a Ph.D. candidate in Electrical and Computer Engineering at The Ohio State University. He received his B.S. degree in Electronic Engineering and M.S. degree in Communication Engineering, both from Xiamen University, China, in 2005 and 2008, respectively. Between 2008 and 2009, he was with the University of Texas at Arlington. He received the Presidential Fellowship from The Ohio State University and Chinese Government Award for Outstanding Ph.D. Students Abroad in 2013. His research interests include wireless communication and networks, smart grids, resource allocation and management, distributed algorithm design, queueing theory, and optimization theory.