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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106685


    Title: EfficientWireless Charger Deployment for Wireless Rechargeable Sensor Networks
    Authors: 江振瑞;Jiang, Jehn-Ruey;Liao, Ji-Hau
    Contributors: 資訊電機學院資訊工程學系
    Keywords: Algorithms;charger deployment;Charging;Covering;directional antennas;Electronic devices;Energy;energy harvesting;Friis transmission equation;greedy algorithms;Mathematical models;Networks;Radio frequency;Sensors;Sustainability;Wireless networks;wireless rechargeable sensor network (WRSN)
    Date: 2016-09-01
    Issue Date: 2026-04-23 13:36:21 (UTC+8)
    Publisher: MDPI Multidisciplinary Digital Publishing Institute;Basel: MDPI AG
    Abstract: 摘要: A wireless rechargeable sensor network (WRSN) consists of sensor nodes that can harvest energy emitted from wireless chargers for refilling their batteries so that the WRSN can operate sustainably. This paper assumes wireless chargers are equipped with directional antennas, and are deployed on grid points of a fixed height to propose two heuristic algorithms solving the following wireless charger deployment optimization (WCDO) problem: how to deploy as few as possible chargers to make the WRSN sustainable. Both algorithms model the charging space of chargers as a cone and calculate charging efficiency according power regression expressions complying with the Friis transmission equation. The two algorithms are the greedy cone covering (GCC) algorithm and the adaptive cone covering (ACC) algorithm. The GCC (respectively, ACC) algorithm greedily (respectively, adaptively) generates candidate cones to cover as many as possible sensor nodes. Both algorithms then greedily select the fewest number of candidate cones, each of which corresponds to the deployment of a charger, to have approximate solutions to the WCDO problem. We perform experiments, conduct simulations and do analyses for the algorithms to compare them in terms of the time complexity, the number of chargers deployed, and the execution time.
    出版者: Basel: MDPI AG
    出版日期: 2016-09-01
    出處: Energies (Basel), 2016-09, Vol.9 (9), p.696-696
    資源來源: Publicly Available Content Database
    版權: Copyright MDPI AG 2016
    識別號: ISSN: 1996-1073
    識別號: EISSN: 1996-1073
    識別號: DOI: 10.3390/en9090696
    Appears in Collections:[Department of Computer Science and information Engineering] journal & Dissertation

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