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Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment
Lifetime optimization is one of the key issues among the many challenges of wireless sensor networks. The introduction of a small number of high-performance relay nodes can effectively improve the quality of the network services. However, how to deploy these nodes reasonably to fully enhance the net...
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/PMC9694288/ https://www.ncbi.nlm.nih.gov/pubmed/36433512 http://dx.doi.org/10.3390/s22228916 |
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author | Yu, Wenjie Li, Xiangmei Zeng, Zhi Luo, Miao |
author_facet | Yu, Wenjie Li, Xiangmei Zeng, Zhi Luo, Miao |
author_sort | Yu, Wenjie |
collection | PubMed |
description | Lifetime optimization is one of the key issues among the many challenges of wireless sensor networks. The introduction of a small number of high-performance relay nodes can effectively improve the quality of the network services. However, how to deploy these nodes reasonably to fully enhance the network lifetime becomes a very difficult problem. In this study, a modified and enhanced Artificial Bee Colony is proposed to maximize the lifetime of a two-tiered wireless sensor network by optimal deployment of relay nodes. First, the dimension of the problem is introduced into the candidate search equation and the local search is adjusted according to the fitness of the problem and number of iterations, which helps to balance the exploration and exploitation ability of the algorithm. Second, in order to prevent the algorithm from falling into local convergence, a dynamic search balance strategy is proposed instead of the scout bee phase in the original Artificial Bee Colony. Then, a feasible solution formation method is proposed to ensure that the relay nodes can form the upper-layer backbone of the network. Finally, we employ this algorithm on a test dataset obtained from the literature. The simulation results show that the proposed algorithm for two-tiered wireless sensor network lifetime optimization can obtain higher and stable average network lifetime and more reasonable relay node deployment compared to other classical and state-of-the-art algorithms, verifying the competitive performance of the proposed algorithm. |
format | Online Article Text |
id | pubmed-9694288 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96942882022-11-26 Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment Yu, Wenjie Li, Xiangmei Zeng, Zhi Luo, Miao Sensors (Basel) Article Lifetime optimization is one of the key issues among the many challenges of wireless sensor networks. The introduction of a small number of high-performance relay nodes can effectively improve the quality of the network services. However, how to deploy these nodes reasonably to fully enhance the network lifetime becomes a very difficult problem. In this study, a modified and enhanced Artificial Bee Colony is proposed to maximize the lifetime of a two-tiered wireless sensor network by optimal deployment of relay nodes. First, the dimension of the problem is introduced into the candidate search equation and the local search is adjusted according to the fitness of the problem and number of iterations, which helps to balance the exploration and exploitation ability of the algorithm. Second, in order to prevent the algorithm from falling into local convergence, a dynamic search balance strategy is proposed instead of the scout bee phase in the original Artificial Bee Colony. Then, a feasible solution formation method is proposed to ensure that the relay nodes can form the upper-layer backbone of the network. Finally, we employ this algorithm on a test dataset obtained from the literature. The simulation results show that the proposed algorithm for two-tiered wireless sensor network lifetime optimization can obtain higher and stable average network lifetime and more reasonable relay node deployment compared to other classical and state-of-the-art algorithms, verifying the competitive performance of the proposed algorithm. MDPI 2022-11-18 /pmc/articles/PMC9694288/ /pubmed/36433512 http://dx.doi.org/10.3390/s22228916 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 Yu, Wenjie Li, Xiangmei Zeng, Zhi Luo, Miao Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment |
title | Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment |
title_full | Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment |
title_fullStr | Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment |
title_full_unstemmed | Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment |
title_short | Problem Characteristics and Dynamic Search Balance-Based Artificial Bee Colony for the Optimization of Two-Tiered WSN Lifetime with Relay Nodes Deployment |
title_sort | problem characteristics and dynamic search balance-based artificial bee colony for the optimization of two-tiered wsn lifetime with relay nodes deployment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9694288/ https://www.ncbi.nlm.nih.gov/pubmed/36433512 http://dx.doi.org/10.3390/s22228916 |
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