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On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks
Nowadays, wireless energy transfer (WET) is a new strategy that has the potential to essentially resolve energy and lifespan issues in a wireless sensor network (WSN). We investigate the process of a wireless energy transfer-based wireless sensor network via a wireless mobile charging device (WMCD)...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749933/ https://www.ncbi.nlm.nih.gov/pubmed/35009926 http://dx.doi.org/10.3390/s22010384 |
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author | Mukase, Sandrine Xia, Kewen Umar, Abubakar Owoola, Eunice Oluwabunmi |
author_facet | Mukase, Sandrine Xia, Kewen Umar, Abubakar Owoola, Eunice Oluwabunmi |
author_sort | Mukase, Sandrine |
collection | PubMed |
description | Nowadays, wireless energy transfer (WET) is a new strategy that has the potential to essentially resolve energy and lifespan issues in a wireless sensor network (WSN). We investigate the process of a wireless energy transfer-based wireless sensor network via a wireless mobile charging device (WMCD) and develop a periodic charging scheme to keep the network operative. This paper aims to reduce the overall system energy consumption and total distance traveled, and increase the ratio of charging device vacation time. We propose an energy renewable management system based on particle swarm optimization (ERMS-PSO) to achieve energy savings based on an investigation of the total energy consumption. In this new strategy, we introduce two sets of energies called emin (minimum energy level) and ethresh (threshold energy level). When the first node reaches the emin, it will inform the base station, which will calculate all nodes that fall under ethresh and send a WMCD to charge them in one cycle. These settled energy levels help to manage when a sensor node needs to be charged before reaching the general minimum energy in the node and will help the network to operate for a long time without failing. In contrast to previous schemes in which the wireless mobile charging device visited and charged all nodes for each cycle, in our strategy, the charging device should visit only a few nodes that use more energy than others. Mathematical outcomes demonstrate that our proposed strategy can considerably reduce the total energy consumption and distance traveled by the charging device and increase its vacation time ratio while retaining performance, and ERMS-PSO is more practical for real-world networks because it can keep the network operational with less complexity than other schemes. |
format | Online Article Text |
id | pubmed-8749933 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87499332022-01-12 On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks Mukase, Sandrine Xia, Kewen Umar, Abubakar Owoola, Eunice Oluwabunmi Sensors (Basel) Article Nowadays, wireless energy transfer (WET) is a new strategy that has the potential to essentially resolve energy and lifespan issues in a wireless sensor network (WSN). We investigate the process of a wireless energy transfer-based wireless sensor network via a wireless mobile charging device (WMCD) and develop a periodic charging scheme to keep the network operative. This paper aims to reduce the overall system energy consumption and total distance traveled, and increase the ratio of charging device vacation time. We propose an energy renewable management system based on particle swarm optimization (ERMS-PSO) to achieve energy savings based on an investigation of the total energy consumption. In this new strategy, we introduce two sets of energies called emin (minimum energy level) and ethresh (threshold energy level). When the first node reaches the emin, it will inform the base station, which will calculate all nodes that fall under ethresh and send a WMCD to charge them in one cycle. These settled energy levels help to manage when a sensor node needs to be charged before reaching the general minimum energy in the node and will help the network to operate for a long time without failing. In contrast to previous schemes in which the wireless mobile charging device visited and charged all nodes for each cycle, in our strategy, the charging device should visit only a few nodes that use more energy than others. Mathematical outcomes demonstrate that our proposed strategy can considerably reduce the total energy consumption and distance traveled by the charging device and increase its vacation time ratio while retaining performance, and ERMS-PSO is more practical for real-world networks because it can keep the network operational with less complexity than other schemes. MDPI 2022-01-05 /pmc/articles/PMC8749933/ /pubmed/35009926 http://dx.doi.org/10.3390/s22010384 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Mukase, Sandrine Xia, Kewen Umar, Abubakar Owoola, Eunice Oluwabunmi On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks |
title | On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks |
title_full | On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks |
title_fullStr | On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks |
title_full_unstemmed | On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks |
title_short | On-Demand Charging Management Model and Its Optimization for Wireless Renewable Sensor Networks |
title_sort | on-demand charging management model and its optimization for wireless renewable sensor networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8749933/ https://www.ncbi.nlm.nih.gov/pubmed/35009926 http://dx.doi.org/10.3390/s22010384 |
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