Hierarchical Threshold Routing Protocol for Enhancing Energy Efficiency in Heterogeneous Wireless Sensor Networks

WSN deployment and operation require overcoming various obstacles. Data security, endurance of batteries, and connectivity are these concerns. Since sensor nodes are commonly put in distant and inaccessible regions, constant replacement of batteries or recharging is impracticable. Transmission range limits coverage and the network's capacity to gather data from far nodes. Wireless communications might be eavesdropped; hence data security is essential to secure critical network data. To address these issues, the thesis designs WSN protocols that maximize energy savings, coverage, connection, and intruder protection. In this study, distance and energy are key characteristics for energy-efficient routing strategies in diverse networks. A node's remaining power and distance proportions to the overall energy consumption at the level in question and the total amount of each node's separation from the starting station constitute these metrics. Energy-Efficient Transport Protocol Utilizing Threshold Hierarchy (EEPH) yields better results than TSEP. The Hybrid Grey Wolf Optimizing Method (HGWOM) framework we created leverages probability-based cluster leader selection. Grey Wolf Optimization (GWO) optimizes the structure. A GWOLEACH hybrid finds the fittest junction based on remaining energy and the nearest base station distance. Experiments comparing HGWOM to LEACH and TSEP showed improved network reliability and high packets delivery ratio.