Metaheuristic Approaches for Energy Efficiency and Network Lifetime Optimization in Wireless Sensor Networks

This paper focuses on traditional and natureinspired metaheuristic algorithms, such as Low-Energy Adaptive Clustering Hierarchy (LEACH), Particle Swarm Optimization (PSO) in Wireless Sensor Networks (WSNs). The evaluation focuses on key parameters like network lifetime, node clustering, and energy consumption levels. Results indicate that PSO consistently outperform the LEACH algorithm in these metrics However, the Adaptive Whale Optimization Algorithm (AWOA) is competitive with the PSO algorithm with its results leaning towards on the better side. The study complements related research on the application of swarm intelligence in WSN by focusing on routing optimization, energy aware protocols and centralized clustering of nodes.