Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks

  • Mariem Ayedi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

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.

Original languageEnglish
Article numbere1357
JournalPeerJ Computer Science
Volume9
DOIs
StatePublished - 2023
Externally publishedYes

Keywords

  • Chaotic theory
  • Crossover algorithm
  • Multi-relay underground wireless sensor networks
  • Relay selection
  • Resource efficiency
  • Salp swarm algorithm

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