Particle Swarm optimization based Mobile Sink Routing Protocol in Wireless Sensor Networks

Abstract

With the continuous application of Internet of Things (IoT) technology, cluster-based wireless sensor networks have been the popular solutions for energy saving. However, it commonly faces the challenge of hot spot problem. Hence, designing an efficient and energy-conserving routing strategy for networks is crucial. Static base stations consume considerable energy in routing. Therefore, this paper proposes a cluster routing protocol integrating a mobile sink, aiming to achieve a balanced distribution of energy consumption and maximize network lifetime. Initially, a weighted function is designed based on residual energy, inter-node distance, and node centrality to select Cluster Heads (CH). Subsequently,combining Particle Swarm Optimization (PSO) algorithm, paths are planned for the mobile sink (MS) to efficiently traverse and collect data from the CHs. Additionally, Differential Evolution (DE) is incorporated to prevent the algorithm from falling into local optima. Simulation results demonstrate that compared to other algorithms, the proposed approach consumes less energy and extends the network's lifetime.