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Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks
Achieving a balanced energy and spectral resource utilization is an interesting key design to extend the lifetime of underground wireless sensor networks (UWSNs) where sensor nodes are equipped with small limited energy batteries and communicate through a challenging soil environment. In this articl...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280650/ https://www.ncbi.nlm.nih.gov/pubmed/37346654 http://dx.doi.org/10.7717/peerj-cs.1357 |
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author | Ayedi, Mariem |
author_facet | Ayedi, Mariem |
author_sort | Ayedi, Mariem |
collection | PubMed |
description | Achieving a balanced energy and spectral resource utilization is an interesting key design to extend the lifetime of underground wireless sensor networks (UWSNs) where sensor nodes are equipped with small limited energy batteries and communicate through a challenging soil environment. In this article, we apply an improved meta-heuristic algorithm, based on the Salp Swarm Algorithm (SSA), for multi-relay UWSNs where cooperative relay nodes amplify and forward sensed data, received from the buried source nodes, to the aboveground base station. Hence, the optimal nodes transmission powers, maximizing the network resource efficiency, are obtained and used to select beneficial relay nodes. The algorithm enhances the standard SSA by considering the chaotic map for salps population initialization and the uniform crossover technique for salps positions updates. Simulation results show that the proposed algorithm significantly outperforms the SSA in resource efficiency optimization and network lifetime extension. The obtained gain increases when the number of cooperative relay nodes increases. Furthermore, simulations prove the efficiency of the proposed algorithm against other meta-heuristic algorithms. |
format | Online Article Text |
id | pubmed-10280650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102806502023-06-21 Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks Ayedi, Mariem PeerJ Comput Sci Computer Networks and Communications Achieving a balanced energy and spectral resource utilization is an interesting key design to extend the lifetime of underground wireless sensor networks (UWSNs) where sensor nodes are equipped with small limited energy batteries and communicate through a challenging soil environment. In this article, we apply an improved meta-heuristic algorithm, based on the Salp Swarm Algorithm (SSA), for multi-relay UWSNs where cooperative relay nodes amplify and forward sensed data, received from the buried source nodes, to the aboveground base station. Hence, the optimal nodes transmission powers, maximizing the network resource efficiency, are obtained and used to select beneficial relay nodes. The algorithm enhances the standard SSA by considering the chaotic map for salps population initialization and the uniform crossover technique for salps positions updates. Simulation results show that the proposed algorithm significantly outperforms the SSA in resource efficiency optimization and network lifetime extension. The obtained gain increases when the number of cooperative relay nodes increases. Furthermore, simulations prove the efficiency of the proposed algorithm against other meta-heuristic algorithms. PeerJ Inc. 2023-04-27 /pmc/articles/PMC10280650/ /pubmed/37346654 http://dx.doi.org/10.7717/peerj-cs.1357 Text en ©2023 Ayedi https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Computer Networks and Communications Ayedi, Mariem Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
title | Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
title_full | Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
title_fullStr | Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
title_full_unstemmed | Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
title_short | Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
title_sort | enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks |
topic | Computer Networks and Communications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280650/ https://www.ncbi.nlm.nih.gov/pubmed/37346654 http://dx.doi.org/10.7717/peerj-cs.1357 |
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