计算机网络和信息集成教育部重点实验室(东南大学)

 
   



2018年学术报告


--- 2018年学术报告
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<strong>Charging Utility Maximization in Wireless Rechargeable Sensor Networks by Charging Multiple Sensors Simultaneously</strong>

时间:2018年12月6日 上午10:00 地点:九龙湖计算机楼313

报告简介:

  Wireless energy charging has been regarded as a promising technology for prolonging sensor lifetime in Wireless Rechargeable Sensor Networks (WRSNs). Most existing studies focused on one-to-one charging between a mobile charger and a sensor that suffers charging scalability and efficiency issues. A new charging technique -- one-to-many charging scheme that allows multiple sensors to be charged simultaneously by a single charger can well address the issues. In this paper, we investigate the use of a mobile charger to charge multiple sensors simultaneously in WRSNs under the energy capacity constraint on the mobile charger. We aim to minimize the sensor energy expiration time by formulating a novel charging utility maximization problem, where the amount of utility gain by charging a sensor is proportional to the amount of energy received by the sensor. We also consider the charging tour length minimization problem of minimizing the travel distance of the mobile charger if all requested sensors must be charged, assuming that the mobile charger has sufficient energy to support all requested sensor charging and itself travelling. Specifically, in this paper we first devise an approximation algorithm with a constant approximation ratio for the charging utility maximization problem if the energy consumption of the mobile charger on its charging tour is negligible. Otherwise, we develop an efficient heuristic for it through a non-trivial reduction from a length-constrained utility maximization problem. We then devise the very first approximation algorithm with a constant approximation ratio for the charging tour length minimization problem through exploiting the combinatorial property of the problem. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are promising, and outperform the other heuristics in various settings.

报告人简介:

   Weifa Liang received the PhD degree from the Australian National University in 1998, the M.Eng degree from the University of Science and Technology of China in 1989, and the BSc degree from Wuhan University, China in 1984, all in Computer Science. He is currently a Full Professor in the Research School of Computer Science at the Australian National University. His research interests include design and analysis of energy efficient routing protocols for wireless ad hoc and sensor networks, mobile edge computing, cloud computing, Software-Defined Networking and Virtualized Network Function, design and analysis of parallel and distributed algorithms, approximation algorithms, combinatorial optimization, and graph theory. He is a senior member of the IEEE and a member of the ACM.
   

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