OPTIMIZING WIRELESS SENSOR NETWORKS (WSNS) LIFETIME AND PERFORMANCE WITH AI-ENHANCED CRT-LEACH ROUTING PROTOCOLS

Abstract

This study proposes an advanced routing protocol for Wireless Sensor Networks (WSNs), integrating the principles of the Chinese Remainder Theorem (CRT) with the efficiency of the Low-Energy Adaptive Clustering Hierarchy (LEACH) algorithm, enhanced further with artificial intelligence (AI) techniques, named AI-Powered CRT-LEACH. WSNs, characterized by their deployment in vast and often hostile environments, face significant challenges such as energy constraints, hardware limitations, communication errors, and susceptibility to malicious attacks. These challenges necessitate the development of routing protocols that not only minimize energy consumption but also ensure speed and reliability in data transmission. The AI-Powered CRT-LEACH protocol is designed to address these critical issues by incorporating CRT-based packet splitting for improved message reliability and employing AI for dynamic optimization of routing paths and cluster-head selection. This novel approach aims to significantly reduce energy consumption during communication, extend the network's operational lifespan, and enhance the overall performance of WSNs. Experimental simulations demonstrate that the AI-Powered CRT-LEACH protocol outperforms existing routing protocols in terms of energy efficiency, transmission speed, hardware optimization, and adaptation to real-time changes in the network. By effectively mitigating the inherent vulnerabilities of sensor nodes and optimizing network resources, the proposed protocol offers a robust solution to the operational challenges of WSNs, paving the way for more reliable and efficient environmental monitoring and physical situation observation in various applications.