Topology Control Using Optimized Clustering Scheme in Mobile Ad Hoc Network

Abstract

Due to mobile nodes (MNs), the topology of mobile ad hoc networks (MANETs) frequently varies. Clustering techniques are suggested as a solution to this. Grouping MNs in a MANET has the benefit of reducing congestion and making topology repairs simple. Clustered MN dividing is a multi-objective optimization problem when the MANET size is huge. MANET is partitioned into clusters using a variety of evolutionary methods, including genetic algorithms (GAs). GA has early convergence. Thus, an improved rabbit optimization algorithm (IROA)-based clustering is presented in this work. Using this algorithm, cluster heads (CHs) are selected. Besides, multi-objective functions are used in this algorithm for selecting suitable CHs. Based on the selected CHs, clusters are formed. To manage the topology after clustering, cluster maintenance phase is included. Simulation results of the article depict that the proposed clustering scheme achieves better throughput and energy efficiency.