计算机科学 ›› 2017, Vol. 44 ›› Issue (1): 140-144.doi: 10.11896/j.issn.1002-137X.2017.01.027

• 网络与通信 • 上一篇    下一篇

射频能量捕获异构无线传感网的能量源最少化布置方法

池凯凯,朱留栓,程珍,田贤忠   

  1. 浙江工业大学计算机科学与技术学院 杭州310023;浙江省可视媒体智能处理技术研究重点实验室 杭州310023,浙江工业大学计算机科学与技术学院 杭州310023,浙江工业大学计算机科学与技术学院 杭州310023,浙江工业大学计算机科学与技术学院 杭州310023
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金(61472367,5),浙江省自然科学基金(LY15F020029,LY15F020027)资助

Minimal Energy Transmitters Placement Approaches for RF-energy Harvesting Heterogeneous Wireless Sensor Networks

CHI Kai-kai, ZHU Liu-shuan, CHENG Zhen and TIAN Xian-zhong   

  • Online:2018-11-13 Published:2018-11-13

摘要: 电池供电的无线传感器网络的应用由于电池更换的不便利甚至不可能而受到极大的限制。考虑具有射频能量捕获能力的异构无线传感器网络,网络节点的能量捕获输出功率需求不一样。在已知传感节点数目和位置的情况下,研究如何布置射频能量源(Energy Transmitters,ETs)从而满足所有节点的能量捕获输出功率需求并且最小化ETs数目。首先建模出该最少化ETs的布置问题,为深入了解该问题提供了理论基础;然后提出了一种复杂度较低的贪婪式ETs布置方法和一种复杂度略高些的基于粒子群优化的ETs布置方法。仿真结果表明,与贪婪式方法相比,基于粒子群优化的方法能找到ETs略微更少的布置方案,但其由于复杂度略高,因此可用于节点数目不是很多的场景,而贪婪式方法则可用于节点数目较多的场景。

关键词: 异构无线传感器网络,射频能量捕获,能量源布置,粒子群优化

Abstract: The applications of battery-powered wireless sensor networks are greatly restricted by the inconvenient or even impossible battery replacement.This paper considered the RF-energy harvesting heterogeneous wireless sensor networks where different sensor nodes may have different requirements on the power output of energy harvesting,and studied how to place the energy transmitters (ETs) so that the power output requirements of all nodes are satisfied and the number of ETs is minimized at the same time.This paper first formulated this ETs placement problem so as to deeply and theoretically understand this problem,and then presented a low-complexity greedy scheme and a particle swarm optimization (PSO)-based scheme with relatively high complexity.Simulation results demonstrate that,compared to the greedy scheme,the PSO-based scheme is able to slightly reduce the average number of ETs.However,as the PSO-based scheme is with relatively high complexity,it can be used for the scenarios with not many nodes,whereas the greedy scheme can be used for the scenarios with a large number of nodes.

Key words: Heterogeneous wireless sensor networks,RF energy harvesting,Energy transmitter placement,Particle swarm optimization

[1] SAMPLE A P,YEAGER D J,POWLEDGE P S,et al.Design of an RFID-based battery-free programmable sensing platform [J].IEEE Trans.Instrum.Meas.,2008,57(11):2608-2615.
[2] PARKS A N,LIU A,GOLLAKOTA S,et al.Turbocharging am-bient backscatter communication [C]∥Proc.ACM SIGCOMM.ACM,2014:619-630.
[3] EROL-KANTARCI M,MOUFTAH H T.Mission-aware placement of RF-based power transmitters in wireless sensor networks [C]∥IEEE ISCC.IEEE,2012:12-17.
[4] HE S,CHEN J,JIANG F,et al.Energy provisioning in wireless rechargeable sensor networks[J].IEEE Transactions Mobile Computing,2013,12(10):1931-1942.
[5] FU L,CHENG P,GU Y,et al.Minimizing charging delay inwireless rechargeable sensor networks [C]∥Proc.IEEE INFOCOM.IEEE,2013:2922-2930.
[6] LI Y,FU L,CHEN M,et al.RF-Based Charger Placement for Duty Cycle Guarantee in Battery-Free Sensor Networks [J].IEEE Communications Letters,2015,19(10):1802-1805.
[7] KENNEDY J.Particle swarm optimization.Encyclopedia of Machine Learning [M].New York,NY,USA:Springer-Verlag,2010:760-766.

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