Gaussian-based Improved Power-Aware Routing with Balanced Grouping in Sensor Mesh Networks

Prolonging the network lifetime has been crucial since wireless sensor networks have limited resources interest. One effective method of routing is clustering-based hierarchical routing, finding the ideal quantity of cluster heads has posed a challenge. This paper employs two hierarchical fuzzy logics to assess the suitability of sensors to function as cluster heads. Relevance, proximity to the base station, and separation of cluster heads are among these criteria. The simulation yields five metrics reveal that the suggested strategy uses less energy and approximately 54% longer network life compared to different algorithms. Energy parameters are used to define each network node. Energy is used throughout each network communication to some extent. The goal of the ECHGRP(Energy Clustering Head Gaussian Routing Protocol)proposed work is to extend the life of the network by maximizing connection while utilizing the notion of prioritizing and mobile base stations via circular paths in a clustered network. Each communication node will be prioritized, and this is done based on parametric considerations including connectivity, residual energy, and distance. Remaining energy will serve as the basis for the initial prioritizing. High energy is taken into consideration when choosing a cluster head. The fuzzy logic technique will be used to make all prioritized decisions. The nodes in the base station's sensing range will turn on and engage in direct communication with it whenever it updates its location since the base station has a set communication range.