Title: Optimal path selection for mobile sink using Henry gas particle swarm optimisation and energy prediction based on deep residual network

Authors: Aparna Ashok Kamble; Balaji M. Patil

Addresses: School of Computer Engineering and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, 411029, India ' School of Computer Engineering and Technology, Dr. Vishwanath Karad MIT World Peace University, Pune, Maharashtra, 411029, India

Abstract: The advantage of wireless sensor network (WSN) anywhere at any time makes it one of the popular technologies. Due to the limitation of wireless links, it is necessary to select the optimal path for packet transmission. The most prominent issues faced by the WSN are energy availability and reliability. The energy prediction among the nodes acts as a significant factor to achieve reliability. Hence, this research proposes a mechanism for optimal path selection of MS nodes using a proposed approach named the Henry gas particle swarm optimisation (HGPSO) algorithm. Here, the hybrid Harris hawk salp swarm optimisation (HHSSO) model along with the MS policy is employed for performing the CH selection effectively and is referred to as EE-hHHSS. The deep residual network (DRN) is exploited to predict energy. The proposed HGPSO-based DRN has achieved a maximum packet delivery ratio (PDR) of 42.121%, maximum residual energy of 0.083 J, minimum delay of 0.0000027089 sec, minimum path distance of 13.357, and maximum number of alive nodes is 48 while analysing 50 nodes.

Keywords: wireless sensor network; WSN; particle swarm optimisation; PSO; Henry gas solubility optimisation; HGSO; mobility model; cluster head selection; CH; deep residual network; DRN; packet delivery ratio; PDR.

DOI: 10.1504/IJBIC.2025.149061

International Journal of Bio-Inspired Computation, 2025 Vol.26 No.2, pp.102 - 118

Accepted: 19 Oct 2024
Published online: 13 Oct 2025 *

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