TY - JOUR
T1 - Enhanced meta-heuristic optimization of resource efficiency in multi-relay underground wireless sensor networks
AU - Ayedi, Mariem
N1 - Publisher Copyright:
© Copyright 2023 Ayedi
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Chaotic theory
KW - Crossover algorithm
KW - Multi-relay underground wireless sensor networks
KW - Relay selection
KW - Resource efficiency
KW - Salp swarm algorithm
UR - https://www.scopus.com/pages/publications/85159789811
U2 - 10.7717/PEERJ-CS.1357
DO - 10.7717/PEERJ-CS.1357
M3 - Article
AN - SCOPUS:85159789811
SN - 2376-5992
VL - 9
JO - PeerJ Computer Science
JF - PeerJ Computer Science
M1 - e1357
ER -