This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective.
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Kehao Wang received the B.S degree in Electrical Engineering, M.S. degree in Communication and Information System from Wuhan University of Technology, Wuhan, China, in 2003 and 2006, respectively, and Ph.D in the Department of Computer Science, the University of Paris-Sud XI, Orsay, France, in 2012. From Feb. 2013 to Aug. 2013, he was a postdoc with the HongKong Polytechnic University. In 2013, he joined the School of Information Engineering at the Wuhan University of Technology. From 2015 to 2018, he had been a visiting scholar in the Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA. USA. His research interests are stochastic optimization, operation research, scheduling, wireless network communications, and embedded operating system.
This book provides foundations for the understanding and design of computation-efficient algorithms and protocols for those interactions with environment, i.e., wireless communication systems. The book provides a systematic treatment of the theoretical foundation and algorithmic tools necessarily in the design of computation-efficient algorithms and protocols in stochastic scheduling. The problems addressed in the book are of both fundamental and practical importance. Target readers of the book are researchers and advanced-level engineering students interested in acquiring in-depth knowledge on the topic and on stochastic scheduling and their applications, both from theoretical and engineering perspective.
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