Energy And Load Balancing Platform Based Smart Routing Protocol For WSN

Abstract

The lifetime of a wireless sensor network is greatly influenced by three key factors: clustering nodes, determining routing patterns, and cluster maintenance. In order to enhance network load balancing and energy efficiency, a clustering routing protocol with fuzzy logic is presented in this study along with these three properties. By determining the best possible route, the routing algorithm is used to determine the optimal routing paths and to choose the best cluster heads (CHs). The algorithm converges swiftly thanks to fuzzy logic rules based primarily on a unique fitness function that takes load balancing and lowest energy usage into account together with new determination conditions. Additionally, an adaptive behavior that takes load balance and energy into account is offered to sustain the clusters and further minimize energy use. According to simulation results, the suggested strategy outperforms LEACH, PEGASIS, and Q Learning based routing in terms of longevity, load balancing, convergence speed, and energy efficiency.