Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks

In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCV...

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Main Authors: Ping Zhong, Ya-Ting Li, Wei-Rong Liu, Gui-Hua Duan, Ying-Wen Chen, Neal Xiong
Format: Article
Language:English
Published: MDPI AG 2017-08-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/17/8/1881
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spelling doaj-10ed374baabd433588b769356a39b2022020-11-24T21:04:31ZengMDPI AGSensors1424-82202017-08-01178188110.3390/s17081881s17081881Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor NetworksPing Zhong0Ya-Ting Li1Wei-Rong Liu2Gui-Hua Duan3Ying-Wen Chen4Neal Xiong5School of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaCollege of Computer, National University of Defense Technology, Changsha 410073, ChinaSchool of Information Science and Engineering, Central South University, Changsha 410083, ChinaIn wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs’ movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.https://www.mdpi.com/1424-8220/17/8/1881data collectionwireless chargingnetwork partitionadaptive anchor selection algorithmoptimization function
collection DOAJ
language English
format Article
sources DOAJ
author Ping Zhong
Ya-Ting Li
Wei-Rong Liu
Gui-Hua Duan
Ying-Wen Chen
Neal Xiong
spellingShingle Ping Zhong
Ya-Ting Li
Wei-Rong Liu
Gui-Hua Duan
Ying-Wen Chen
Neal Xiong
Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks
Sensors
data collection
wireless charging
network partition
adaptive anchor selection algorithm
optimization function
author_facet Ping Zhong
Ya-Ting Li
Wei-Rong Liu
Gui-Hua Duan
Ying-Wen Chen
Neal Xiong
author_sort Ping Zhong
title Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks
title_short Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks
title_full Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks
title_fullStr Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks
title_full_unstemmed Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks
title_sort joint mobile data collection and wireless energy transfer in wireless rechargeable sensor networks
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2017-08-01
description In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs’ movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.
topic data collection
wireless charging
network partition
adaptive anchor selection algorithm
optimization function
url https://www.mdpi.com/1424-8220/17/8/1881
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