Enhancing Energy Efficient Routing Protocol for Wireless Sensor Network using Swarm Intelligence
Abstract
Wireless Sensor Networks (WSNs) are characterized by limited energy, and energy efficiency is one of thekey design issues for routing protocols. This research aims to enhance the routing efficiency of dragonflyswarm routing by optimizing route and cluster head selection through the integration of the latest SwarmIntelligence (SI) algorithm, specifically the Dragonfly Algorithm (DA). The proposed method wassystematically compared with the traditional Particle Swarm Optimization (PSO) by measuring energyefficiency, execution time, and packet delivery ratio. Simulation results showed that the DragonflyAlgorithm reduces energy consumption and prolongs network lifetime for classical methods. It exhibitsstrong adaptability to time-varying network topologies and is less likely to be trapped in a local optimum.These results illustrate that SI is a promising technique to help improve the quality of routing protocolsin WSN applied to critical scenarios and offer possibilities for future integration with, for example,machine learning techniques for achieving higher performance.References
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