Journal of Software:2018.29(S1):73-82

(浙江工业大学 计算机科学与技术学院, 浙江 杭州 310023)
Deployment and Transmission Power Optimization of Energy Transmitters in RF Energy Harvesting Wireless Sensor Networks
BIAN Ji-Dong,LIN Yi-Min,CHI Kai-Kai
(School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China)
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Received:May 01, 2018    
> 中文摘要: 射频能量捕获无线传感网(RF energy harvesting wireless sensor network,简称RFEH-WSN)是无线传感网的热点研究领域之一,专用射频能量源设备(energy transmitter,简称ET)的使用进一步增强了网络的可控制性和实用性.这类应用中一个值得研究的问题就是如何配置给定数量的ET,从而在满足节点能量需求的前提下优化布置位置和发送功率,减少能量消耗.首先对ET布置和发送功率联合优化问题建模,明确优化目标和限制条件.然后分别提出了先基于聚类算法确定ET位置再调整功率的分步优化方案,以及基于粒子群优化(particle swarm optimization,简称PSO)的布置与发送功率联合优化方案.仿真结果显示,布置和发送功率联合优化方案较分步优化方案,ET发送功率的节能效果更为明显.
Abstract:RF energy harvesting wireless sensor network (RFEH-WSN) is a recent active research field in the domain of wireless sensor network. The use of dedicated energy transmitter (ET) has further enhanced the controllability and practicability of wireless sensor networks. One issue worth researching in this kind of WSNs is how to configure a given number of ET to optimize transmission power and reduce energy consumption under the premise of meeting node energy requirements. Firstly, the ET placement and power optimization problem are formulated to make clear the optimization objective and constraints. Then two optimization schemes are proposed. One is a two-step optimization scheme by which the transmission power of ET will be adjusted after placing ET. Another scheme is a joint optimization of placement and transmission power based on particle swarm optimization (PSO). Simulation results show that the energy saving effect of the joint optimization scheme is more obvious than that of the other.
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基金项目:国家自然科学基金(61472367,61872322,61432015) 国家自然科学基金(61472367,61872322,61432015)
Foundation items:National Natural Science Foundation of China (61472367,61872322,61432015)
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BIAN Ji-Dong,LIN Yi-Min,CHI Kai-Kai.Deployment and Transmission Power Optimization of Energy Transmitters in RF Energy Harvesting Wireless Sensor Networks.Journal of Software,2018,29(S1):73-82