Abstract:

Abstract Wireless sensor networks (WSNs) often face hot spot problems, where sensor nodes near the sink node handle higher data volumes during transmission, leading to energy depletion and bottleneck issues. Utilizing mobile sink nodes with clustering algorithms is a promising approach to enhance the energy efficiency, network lifetime, and overall performance of wireless sensor networks. Furthermore, the integration of nature-inspired algorithms with the mobile sink strategy has enhanced network performance in terms of latency, energy efficiency, and mobility. Our paper presents a novel clustering algorithm based on the particle swarm optimization (PSO) technique, utilizing mobile sink nodes to mitigate hot spot problems in WSNs. Our proposed EPMS (Energy- aware PSO based routing algorithm with Mobile Sink support) incorporates a virtual clustering technique during the routing process, leveraging the PSO algorithm. The selection of cluster heads is based on key parameters such as residual energy and node position. A well-designed control strategy is employed to enable the mobile sink to efficiently collect data from cluster heads. Simulation results demonstrate that the proposed algorithm offers significant improvements in extension of network performance, expenditure of energy, and reduced transmission delays as compared to several commonly used routing algorithms. By integrating the PSO technique and mobile sink nodes, this research contributes to addressing the hot spot problem in WSNs, offering enhanced network performance and sustainability.

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