Serp: Scalable And Energy Efficient Routing Protocol For Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are widely used in applications such as environmental monitoring, industrial automation, and smart city infrastructure. Despite their growing adoption, energy consumption and maintenance of battery-operated sensor nodes remain significant challenges that limit network lifetime. This paper proposes a hybrid routing protocol combining the energy efficient LEACH protocol for optimized clustering with Particle Swarm Optimization (PSO) and Q-learning algorithms to enhance energy efficiency, scalability, and adaptability in large-scale network deployments. PSO is utilized to identify initial energy-optimal routing paths, while Q-learning adaptively refines routes in real time based on dynamic factors like remaining node energy, congestion levels, and link reliability. Extensive simulations compare the proposed SERP protocol with GA-UCR and I-OEERP protocols, showing superior results in extending network lifetime, reducing overall energy consumption, improving packet delivery ratios, and minimizing network overhead. These improvements demonstrate the protocol’s potential to support sustainable and efficient communications in large-scale Internet of Things (IoT) environments, making it a promising solution for energy-sensitive WSN applications