Fast Convergence Grasshopper Optimization Algorithm based Clustering with Multihop Routing Protocol for Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSN) usually contains numerous sensor nodes, commonly deployed for monitoring and tracking applications. Since the sensor nodes operate on inbuilt battery, energy efficiency becomes a critical design issue in WSN. Clustering and routing are considered as the commonly employed energy efficient techniques. The selection of cluster heads (CHs) and optimal routes are considered as NP hard problem, and metaheuristic algorithms can be employed to resolve it. This paper presents energy efficient Nelder Mead with Grasshopper Optimization Algorithm based Clustering with Multihop Routing (NMGOA-MR) protocol for WSN. The presented model involves two important phases, namely clustering and routing. Initially, NMGOA based clustering process takes place by the use of residual energy, distance to base station (BS), and distance to neighbors. Next, in the second phase, improved ant colony optimization (IACO) based multihop routing protocol is derived for the optimal selection of paths to BS. In ACO, levy distribution mechanism is incorporated into the ACO algorithm to increase the convergence rate. A detailed simulation analysis is carried out to examine the energy efficient and network lifetime performance of the NMGOA-MR technique. The obtained simulation outcome ensured the superior outcome of the presented model over the compared methods.