Nodes clustering and multi-hop routing protocol optimization using hybrid chimp optimization and hunger games search algorithms for sustainable energy efficient underwater wireless sensor networks

Clustering and routing processes in underwater wireless sensor networks (UWSNs) are challenging tasks in the underwater environment due to the multiplicity of sensor nodes, transmission bandwidth, and limited energy resources. In order to address the shortcomings mentioned above, this paper proposes...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Sustainable computing informatics and systems Ročník 35; s. 100731
Hlavní autori: Yang, Yang, Wu, Yunqiang, Yuan, Hongji, Khishe, Mohammad, Mohammadi, Mokhtar
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Inc 01.09.2022
Predmet:
Chimp optimization algorithm
Clustering
Energy efficiency
Hierarchical
Routing
Hierarchical
Routing
Chimp optimization algorithm
Energy efficiency
Clustering
ISSN:2210-5379
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Clustering and routing processes in underwater wireless sensor networks (UWSNs) are challenging tasks in the underwater environment due to the multiplicity of sensor nodes, transmission bandwidth, and limited energy resources. In order to address the shortcomings mentioned above, this paper proposes a novel hybrid Chimp Optimization and Hunger Games Search (ChOA-HGS) algorithms for clustering and multi-hop routing optimization in UWSNs. In this approach, first, the ChOA is used to choose cluster heads and efficiently structure clusters. Then, the HGS-based routing procedure is used to determine the network’s best pathways. The proposed approach combines the advantages of clustering and routing, resulting in optimal network lifetime and energy efficiency. The proposed ChOA-HGS is validated using a variety of measures after it is simulated using three different scenarios. In order to evaluate the performance of the ChOA-HGS, results are compared to PSO, MPSO, IPSO-GWO, TEEN, and LEACH. The results show that the ChOA-HGS outperformed other benchmarks in terms of lifetime and energy consumption. •ChOA is used to choose cluster heads and efficiently structure clusters.•HGS-based routing is used to determine the network’s best pathways.•The proposed approach combines the advantages of clustering and routing.•the outcome is optimal network lifetime and energy efficiency.
ISSN:2210-5379
DOI:10.1016/j.suscom.2022.100731