Energy Efficient Cluster-Based Routing Protocol for Wireless Sensor Network Using Hybrid Bio-Inspired Swarm Intelligence Algorithm
Keywords:
WSN, LEACH, PSO, GSO, FA, Cluster, Routing, MATLABAbstract
Wireless Sensor Networks (WSNs) have gained significant popularity due to advancements in wireless communication enabled by low-cost and low-power sensors. However, since WSN nodes are powered by batteries, they eventually lose their autonomy, limiting the network’s lifespan. This energy constraint impacts the overall network performance. Clustering is a strategy that can enhance network lifetime while reducing energy consumption by grouping similar sensors for data collection and transmission to the Base Station (BS). However, the Cluster Head (CH), responsible for data collection and transfer, consumes more energy, so efficient identification of CHs is crucial for extending the WSN’s lifespan and minimizing energy use. Developing a routing algorithm that addresses the challenges of reducing energy consumption and maximizing network lifetime remains a complex task. This paper introduces an energy-efficient clustering routing protocol based on a hybrid GSO-FF (Global Search Optimization - Firefly) algorithm to address these critical issues in WSNs. The GSO algorithm selects the optimal CH from a set of nodes, while the Firefly optimization algorithm determines the best route between the CH and BS. Simulation results demonstrate that the proposed methodology improves energy consumption by 10.22%, 11.26%, and 14.28%, and normalizes energy by 9.56%, 11.78%, and 13.76%, outperforming existing state-of-the-art approaches.
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