Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network

Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger&rsqu...

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Main Authors: Haolin Liu, Qingyong Deng, Shujuan Tian, Xin Peng, Tingrui Pei
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/7/2223
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author Haolin Liu
Qingyong Deng
Shujuan Tian
Xin Peng
Tingrui Pei
author_facet Haolin Liu
Qingyong Deng
Shujuan Tian
Xin Peng
Tingrui Pei
author_sort Haolin Liu
collection DOAJ
description Wireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger’s limited traveling distance and speed, not every node that needs to be charged may be serviced in time. Thus, in such scenario, how to make a route plan for the mobile charger to determine which nodes should be charged first is a critical issue related to the network’s Quality of Service (QoS). In this paper, we propose a mobile charger’s scheduling algorithm to mitigate the data loss of network by considering the node’s criticality in connectivity and energy. First, we introduce a novel metric named criticality index to measure node’s connectivity contribution, which is computed as a summation of node’s neighbor dissimilarity. Furthermore, to reflect the node’s charging demand, an indicator called energy criticality is adopted to weight the criticality index, which is a normalized ratio of the node’s consumed energy to its total energy. Then, we formulate an optimization problem with the objective of maximizing total weighted criticality indexes of nodes to construct a charging tour, subject to the mobile charger’s traveling distance constraint. Due to the NP-hardness of the problem, a heuristic algorithm is proposed to solve it. The heuristic algorithm includes three steps, which is spanning tree growing, tour construction and tour improvement. Finally, we compare the proposed algorithm to the state-of-art scheduling algorithms. The obtained results demonstrate that the proposed algorithm is a promising one.
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spelling doaj.art-b9601cdb83fc40b78174c20e02dfa7a92022-12-22T04:00:38ZengMDPI AGSensors1424-82202018-07-01187222310.3390/s18072223s18072223Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor NetworkHaolin Liu0Qingyong Deng1Shujuan Tian2Xin Peng3Tingrui Pei4College of Information Engineering, Xiangtan University, Xiangtan 411105, ChinaCollege of Information Engineering, Xiangtan University, Xiangtan 411105, ChinaCollege of Information Engineering, Xiangtan University, Xiangtan 411105, ChinaSchool of Information Science and Technology, Hunan Institute of Science and Technology, Yueyang 414000, ChinaCollege of Information Engineering, Xiangtan University, Xiangtan 411105, ChinaWireless Power Transfer (WPT) technology is considered as a promising approach to make Wireless Rechargeable Sensor Network (WRSN) work perpetually. In WRSN, a vehicle exists, termed a mobile charger, which can move close to sensor nodes and charge them wirelessly. Due to the mobile charger’s limited traveling distance and speed, not every node that needs to be charged may be serviced in time. Thus, in such scenario, how to make a route plan for the mobile charger to determine which nodes should be charged first is a critical issue related to the network’s Quality of Service (QoS). In this paper, we propose a mobile charger’s scheduling algorithm to mitigate the data loss of network by considering the node’s criticality in connectivity and energy. First, we introduce a novel metric named criticality index to measure node’s connectivity contribution, which is computed as a summation of node’s neighbor dissimilarity. Furthermore, to reflect the node’s charging demand, an indicator called energy criticality is adopted to weight the criticality index, which is a normalized ratio of the node’s consumed energy to its total energy. Then, we formulate an optimization problem with the objective of maximizing total weighted criticality indexes of nodes to construct a charging tour, subject to the mobile charger’s traveling distance constraint. Due to the NP-hardness of the problem, a heuristic algorithm is proposed to solve it. The heuristic algorithm includes three steps, which is spanning tree growing, tour construction and tour improvement. Finally, we compare the proposed algorithm to the state-of-art scheduling algorithms. The obtained results demonstrate that the proposed algorithm is a promising one.http://www.mdpi.com/1424-8220/18/7/2223wireless rechargeable sensor networkmobile chargerrecharge schedulecriticality indexheuristic algorithm
spellingShingle Haolin Liu
Qingyong Deng
Shujuan Tian
Xin Peng
Tingrui Pei
Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
Sensors
wireless rechargeable sensor network
mobile charger
recharge schedule
criticality index
heuristic algorithm
title Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
title_full Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
title_fullStr Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
title_full_unstemmed Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
title_short Recharging Schedule for Mitigating Data Loss in Wireless Rechargeable Sensor Network
title_sort recharging schedule for mitigating data loss in wireless rechargeable sensor network
topic wireless rechargeable sensor network
mobile charger
recharge schedule
criticality index
heuristic algorithm
url http://www.mdpi.com/1424-8220/18/7/2223
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AT shujuantian rechargingscheduleformitigatingdatalossinwirelessrechargeablesensornetwork
AT xinpeng rechargingscheduleformitigatingdatalossinwirelessrechargeablesensornetwork
AT tingruipei rechargingscheduleformitigatingdatalossinwirelessrechargeablesensornetwork