Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks

In this article, we study the scheduling of a charging vehicle to replenish sensor energy in a large-scale wireless sensor network, by utilizing the novel wireless energy transfer technology. We note that existing studies do not treat different sensors in the network discriminatively and consider on...

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Main Authors: Tong Li, Tang Liu, Jian Peng, Feng Lin, Wenzheng Xu
Format: Article
Language:English
Published: Hindawi - SAGE Publishing 2018-07-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1177/1550147718784479
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author Tong Li
Tang Liu
Jian Peng
Feng Lin
Wenzheng Xu
author_facet Tong Li
Tang Liu
Jian Peng
Feng Lin
Wenzheng Xu
author_sort Tong Li
collection DOAJ
description In this article, we study the scheduling of a charging vehicle to replenish sensor energy in a large-scale wireless sensor network, by utilizing the novel wireless energy transfer technology. We note that existing studies do not treat different sensors in the network discriminatively and consider only how to charge as many sensors as possible before their energy expirations. However, there are some critical sensors in the network, so that many other sensors have no alternative routing paths to upload their sensing data to the base station if the critical sensors die. Therefore, the energy expiration of a critical sensor will result in that not only the sensor itself cannot continue its monitoring task, but also many other sensors cannot send their data during the dead period of the critical sensor. Then, the monitoring quality of the sensor network will significantly deteriorate due to the energy expirations of the critical sensor. Unlike existing studies, we take into account the impact of energy depletions of critical sensors and investigate a charging scheduling problem for sensor networks, which is to schedule a charging vehicle to replenish a set of to-be-charged sensors, such that not only the amount of lost data by dead sensors is minimized, but also the traveling cost of the vehicle for charging sensors is minimized, too. We then propose a novel algorithm for the problem. We finally compare the proposed algorithm with existing studies and simulation results show that the amount of lost data by the proposed algorithm is only about 50% of those by the existing studies, and the weighted sum of the amount of lost data and the vehicle travel distance is about 70% of those by the existing ones.
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spelling doaj.art-afb38ef40c724eb4a0b5bdda2d34d39c2023-09-03T02:34:07ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772018-07-011410.1177/1550147718784479Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networksTong Li0Tang Liu1Jian Peng2Feng Lin3Wenzheng Xu4College of Computer Science, Sichuan University, Chengdu, ChinaCollege of Fundamental Education, Sichuan Normal University, Chengdu, ChinaCollege of Computer Science, Sichuan University, Chengdu, ChinaCollege of Computer Science, Sichuan University, Chengdu, ChinaCollege of Computer Science, Sichuan University, Chengdu, ChinaIn this article, we study the scheduling of a charging vehicle to replenish sensor energy in a large-scale wireless sensor network, by utilizing the novel wireless energy transfer technology. We note that existing studies do not treat different sensors in the network discriminatively and consider only how to charge as many sensors as possible before their energy expirations. However, there are some critical sensors in the network, so that many other sensors have no alternative routing paths to upload their sensing data to the base station if the critical sensors die. Therefore, the energy expiration of a critical sensor will result in that not only the sensor itself cannot continue its monitoring task, but also many other sensors cannot send their data during the dead period of the critical sensor. Then, the monitoring quality of the sensor network will significantly deteriorate due to the energy expirations of the critical sensor. Unlike existing studies, we take into account the impact of energy depletions of critical sensors and investigate a charging scheduling problem for sensor networks, which is to schedule a charging vehicle to replenish a set of to-be-charged sensors, such that not only the amount of lost data by dead sensors is minimized, but also the traveling cost of the vehicle for charging sensors is minimized, too. We then propose a novel algorithm for the problem. We finally compare the proposed algorithm with existing studies and simulation results show that the amount of lost data by the proposed algorithm is only about 50% of those by the existing studies, and the weighted sum of the amount of lost data and the vehicle travel distance is about 70% of those by the existing ones.https://doi.org/10.1177/1550147718784479
spellingShingle Tong Li
Tang Liu
Jian Peng
Feng Lin
Wenzheng Xu
Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks
International Journal of Distributed Sensor Networks
title Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks
title_full Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks
title_fullStr Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks
title_full_unstemmed Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks
title_short Charge critical sensors first: Minimize data loss in wireless rechargeable sensor networks
title_sort charge critical sensors first minimize data loss in wireless rechargeable sensor networks
url https://doi.org/10.1177/1550147718784479
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AT jianpeng chargecriticalsensorsfirstminimizedatalossinwirelessrechargeablesensornetworks
AT fenglin chargecriticalsensorsfirstminimizedatalossinwirelessrechargeablesensornetworks
AT wenzhengxu chargecriticalsensorsfirstminimizedatalossinwirelessrechargeablesensornetworks