Energy Aware Fine Cluster Head based Routing for Heterogeneous Wireless Sensor Networks using Particle Swarm Optimization and Ant Colony Optimization Algorithms

Reducing a node’s power consumption is a difficult task for extending the network’s lifetime because the nodes are resource-constrained (i.e., limited battery power, processing capacity, storage, and non-rechargeable). Many of the existing cluster-based strategies and algorithms for heterogeneous wireless sensor networks (HWSNs) are failing to adapt to the dynamic nature of the network and energy conservation of the nodes. Recharging or replacing the deployed device drained batteries can be challenging, especially in complex situations. For the network to have a longer lifespan, power preservation is very necessary. The sensor nodes must identify the most effective clustering-based routing method to minimize energy consumption. In this, we propose an improved effective fine cluster head-based routing algorithm for HWSNs, specifically designed for cluster head (CH) and fine cluster head (FCH) selection and re-selection. Compared to ECEEC, EECABCO, LEACH, and EECRP-BOACOA, the proposed technique exhibited a longer network lifespan. The suggested technique was compared against current routing methods as, EECABCO, LEACH, ECEEC, and EECRP-BOACOA. The technique demonstrated superior network performance compared to traditional WSN clustering methods. The proposed approach had 55% living nodes after 2000 rounds, which was far better than the existing methods. The purpose of this algorithm is to minimize network energy usage, overcome sensor node power consumption, and extend the network’s lifespan. © 2024 School of Science, DUTH. All rights reserved.