Scalable and energy efficient routing protocol for wireless sensor networks

Abstract Wireless sensor networks are very important in various fields like environmental monitoring, industrial automation, and smart cities. The small battery of sensor nodes is a major challenge in sensor networks to ensure that the network has a long lifetime. This paper introduces a hybrid routing protocol based on the combination of the energy-aware LEACH protocol to achieve optimal clustering, Particle Swarm Optimization (PSO), and Q-learning to achieve high energy efficiency, scalability, and adaptability in the large-scale WSNs. PSO is used to do the initial exploration of the routes based on energy consumption, and Q-learning is used to refine routes dynamically in real-time using residual energy, congestion, and link reliability. The proposed protocol was highly simulated and compared with GA-UCR and I-OEERP protocols. The findings indicate that the network lifetime, energy usage, packet delivery ratio, and network overhead have been considerably improved, which proves the usefulness of the strategy in the context of large-scale Internet of Things (IoT) use.