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Resource optimization methods are vital to ensuring the deterministic performance of industrial wireless networks. Traditional resource optimization methods adopt the isolated resource optimization methods for each protocol layer, which is inherently local-optimal and leads performance uncontrollable. To focus on “Performance Controllable Industrial Wireless Networks”, this book presents thejoint resource optimization methods across multiple protocol layers for industrial wireless networks; reviews recent, major advances; and discusses the practical implementations of the proposed methods.
The joint resource optimization methods discussed here will greatly benefit scientists and researchers in the areas of industrial automation and Industrial Internet of Things. To gain the most from this book, readers should have a fundamental grasp of wireless communication, scheduling theory, and convex optimization.
Prof. Peng Zeng received the Ph.D. degree in mechatronic engineering from the Graduate School of the Chinese Academy of Sciences, Beijing, China, in 2005. He is currently a Vice Director of Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China. He is also the Director of the Network Control System Key Laboratory, Chinese Academy of Sciences. He has authored or coauthored more than 100 conference papers, journal articles, and book chapters related to his research area and five pending/filed U.S. patents. His research interests include wireless sensor network and industrial communication technologies.
Prof. XiJin received the Ph.D. degree in computer science from Northeastern University, Shenyang, China, in 2013. She is currently a Professor with the Shenyang Institute of Automation, Chinese Academy of Sciences, China. Her research interests include industrial networks, real-time scheduling, Internet of Things, and cyber-physical systems. Prof. Jin is also a senior member of China Computer Federation (CCF) and a committee member of the CCF technical committee on embedded systems.
Prof. Wei Liang received the PhD degree in mechatronic engineering from Shenyang Institute of Automation, Chinese Academy of
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