Trust Based Energy Efficient Routing Design Based on Hybrid Particle Swarm Optimization (HPSO) for Wireless Sensor Networks

Congestion in wireless sensor networks (WSNs) reduces resource availability, often leading to sensor node failures and misbehavior. Additionally, high energy consumption decreases the overall lifespan and performance of the network. To address these limitations, this paper presents a trust-based and congestion-aware optimization method for WSNs. The proposed strategy consists of two main stages. In the first stage, congestion levels and node trust values are evaluated to derive an optimal congestion metric. In the second stage, a Hybrid Particle Swarm Optimization (HPSO) algorithm is applied to determine optimal data routing paths from Sensor Nodes (SNs) to the Base Station (BS), considering both distance and trust-congestion parameters. The proposed HPSO combines the immigration and emigration processes of the Biogeography-Based Optimization (BBO) algorithm with the mutation process of Particle Swarm Optimization (PSO) to achieve efficient data distribution. Experimental comparisons with existing methods demonstrate that the proposed approach significantly improves performance in terms of energy consumption, latency, packet delivery ratio (PDR), and network lifetime.