Optimizing routing in wireless sensor networks: leveraging pond skater and ant colony optimization algorithms

Wireless sensor networks (WSNs) are crucial in collecting environmental information through sensor nodes. However, limited energy resources pose a challenge, necessitating efficient routing algorithms to minimize energy consumption. Failure to address issues can consume energy and reduce network lifespan and overall efficiency. This research paper presents a cutting-edge approach for minimizing the consumption of energy within WSN through the implementation of an optimal routing method. The approach involves two steps: first, clustering sensor nodes using the pond skater algorithm (PSA) to select cluster head (CHs) for routing; second, by leveraging the ant colony optimization (ACO) algorithm, this study introduces an innovative technique that empowers a mobile sink to gather packets from given CHs and transmit effectively, send them back to the base station (BS). Notably, the authors make a significant contribution by introducing a different variant of the PSA algorithm to select CH. This novel approach aims to curtail the consumption of energy within WSN significantly. The authors also present an ACO-based head traversal for cluster method, resembling the traveling salesman problem coding, for minimized energy consumption. The study’s primary objectives include reducing energy consumption, minimizing packet delivery ratio, and prolonging the lifetime of the WSN. The assessment efficacy of the proposed method was achieved by regressive simulations using MATLAB on diverse scenarios. Through meticulous comparative analyses with several efficient algorithms, the method proposed here has shown significant performance in network lifetime comparison of PSACO in terms of Alive nodes with number of rounds PSO: 17.65%, GWO: 25%, CS: 33.33%, CBR-ICWSN: 66.66%, CCP-IC: 17.65%.