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A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks
To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the Mobile Data C...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163808/ https://www.ncbi.nlm.nih.gov/pubmed/30200353 http://dx.doi.org/10.3390/s18092887 |
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author | Sha, Chao Wang, Qi-Wei Zhang, Lu Wang, Ru-Chuan |
author_facet | Sha, Chao Wang, Qi-Wei Zhang, Lu Wang, Ru-Chuan |
author_sort | Sha, Chao |
collection | PubMed |
description | To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the Mobile Data Collectors (MDCs), the network is firstly divided into several regions with the help of the Virtual Scan Line (VSL). Then, the MDCs and the Wireless Charging Vehicles (WCVs) are employed in each region for high efficient data collection and energy replenishment. In order to ensure the integrity of data collection and reduce the rate of packet loss, a speed adjustment scheme for MDC is also proposed. In addition, by calculating the adaptive threshold of the recharging request, those nodes with different energy consumption rates are recharged in a timely way that avoids their premature death. Finally, the limited battery capacity of WCVs and their energy consumption while moving are also taken into account, and an adaptive recharging scheme based on maximum benefit is proposed. Experimental results show that the energy consumption is effectively balanced in DCMRB. Furthermore, this can not only enhance the efficiency of data collection, but also prolong the network lifetime compared with the Energy Starvation Avoidance Online Charging scheme (ESAOC), Greedy Mobile Scheme based on Maximum Recharging Benefit (GMS-MRB) and First-Come First-Served (FCFS) methods. |
format | Online Article Text |
id | pubmed-6163808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61638082018-10-10 A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks Sha, Chao Wang, Qi-Wei Zhang, Lu Wang, Ru-Chuan Sensors (Basel) Article To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the Mobile Data Collectors (MDCs), the network is firstly divided into several regions with the help of the Virtual Scan Line (VSL). Then, the MDCs and the Wireless Charging Vehicles (WCVs) are employed in each region for high efficient data collection and energy replenishment. In order to ensure the integrity of data collection and reduce the rate of packet loss, a speed adjustment scheme for MDC is also proposed. In addition, by calculating the adaptive threshold of the recharging request, those nodes with different energy consumption rates are recharged in a timely way that avoids their premature death. Finally, the limited battery capacity of WCVs and their energy consumption while moving are also taken into account, and an adaptive recharging scheme based on maximum benefit is proposed. Experimental results show that the energy consumption is effectively balanced in DCMRB. Furthermore, this can not only enhance the efficiency of data collection, but also prolong the network lifetime compared with the Energy Starvation Avoidance Online Charging scheme (ESAOC), Greedy Mobile Scheme based on Maximum Recharging Benefit (GMS-MRB) and First-Come First-Served (FCFS) methods. MDPI 2018-08-31 /pmc/articles/PMC6163808/ /pubmed/30200353 http://dx.doi.org/10.3390/s18092887 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sha, Chao Wang, Qi-Wei Zhang, Lu Wang, Ru-Chuan A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks |
title | A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks |
title_full | A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks |
title_fullStr | A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks |
title_full_unstemmed | A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks |
title_short | A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks |
title_sort | high-efficiency data collection method based on maximum recharging benefit in sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163808/ https://www.ncbi.nlm.nih.gov/pubmed/30200353 http://dx.doi.org/10.3390/s18092887 |
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