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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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2023-04-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-1357.pdf |
| _version_ | 1797836919231479808 |
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| author | Mariem Ayedi |
| author_facet | Mariem Ayedi |
| author_sort | Mariem Ayedi |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-09T15:16:37Z |
| format | Article |
| id | doaj.art-e80ca1e887f3442db494157bb622dbd7 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-04-09T15:16:37Z |
| publishDate | 2023-04-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-e80ca1e887f3442db494157bb622dbd72023-04-29T15:05:05ZengPeerJ Inc.PeerJ Computer Science2376-59922023-04-019e135710.7717/peerj-cs.1357Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networksMariem Ayedi0Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-kharj, Saudi ArabiaAchieving 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.https://peerj.com/articles/cs-1357.pdfMulti-relay underground wireless sensor networksResource efficiencyRelay selectionChaotic theoryCrossover algorithmSalp swarm algorithm |
| spellingShingle | Mariem Ayedi Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks PeerJ Computer Science Multi-relay underground wireless sensor networks Resource efficiency Relay selection Chaotic theory Crossover algorithm Salp swarm algorithm |
| 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 | Multi-relay underground wireless sensor networks Resource efficiency Relay selection Chaotic theory Crossover algorithm Salp swarm algorithm |
| url | https://peerj.com/articles/cs-1357.pdf |
| work_keys_str_mv | AT mariemayedi enhancedmetaheuristicoptimizationofresourceefficiencyinmultirelayundergroundwirelesssensornetworks |