Energy-Efficient Intelligent Routing Protocol for Wireless Sensor Networks Using Hybrid PSO-GA Optimization
Keywords:
Wireless Sensor Networks, Energy Efficiency, Routing Protocol, Particle Swarm Optimization, Genetic Algorithm.Abstract
Energy management is a major challenge in Wireless Sensor Networks (WSN), as the limited battery power of sensor nodes directly affects network lifetime. Various studies have focused on energy efficiency through the design of intelligent routing protocols, but most still face problems of load balancing and slow convergence. This study aims to develop a Hybrid Particle Swarm Optimization – Genetic Algorithm (PSO-GA) based intelligent routing protocol to improve energy efficiency and network stability. A quantitative approach was used through MATLAB-based experimental simulations with a first-order radio energy model. The PSO algorithm was used to accelerate convergence, while GA maintained solution diversity so that the system did not get stuck at a local optimum. Simulation results show that Hybrid PSO-GA can reduce energy consumption by up to 25%, extend network lifetime by 32%, increase packet delivery ratio to 96.4%, and reduce average delay to 0.22 seconds compared to conventional protocols. The hybrid approach proves effective in balancing energy consumption between nodes and maintaining communication stability. These results indicate that Hybrid PSO-GA has the potential to become the basis for developing future intelligent routing protocols for WSNs and large-scale IoT applications.
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