Fuzzy-Guided Genetic Algorithm Routing for Energy Conservation in Wireless Sensor Networks

In recent decades, wireless sensor network (WSN) technology has seen a profound metamorphosis, shifting lifestyles from the conventional to the intricate. Nevertheless, preserving the longevity of the network poses a significant challenge in Wireless Sensor Networks (WSN), given the limited resources of interconnected devices. This study delves into routing protocols for sensor networks, presenting an innovative and energy-efficient on-demand multipath distance vector routing approach known as FGGA, leveraging fuzzy algorithm capabilities. The FGGA protocol employs a sophisticated matching calculation function to optimize routes based on node energy usage, thereby enhancing the energy efficiency of WSN. Its effectiveness will be evaluated through thorough comparisons and assessments against established ad hoc routing protocols such as AODV, LEACH-GA, GA-AODV, EPAR, DSR, and EBAR_BFS. The derived experimental findings robustly validate that FGGA offers marked enhancements in wireless network metrics, particularly throughput, packet delivery ratio, and energy usage. In essence, the introduced FGGA protocol, founded on fuzzy algorithms, emerges as a potent solution to the quandary of amplifying network longevity in WSNs. This paper introduces FGGA, a Fuzzy Adaptive Genetic Algorithm tailored for the AOMDV routing protocol, showcasing its novelty in optimizing the fitness function and refining discovered routes.