REALIZATION OF ENERGY EFFICIENT CLUSTERING AND POWER OPTIMIZATION IN VANET – A COMPARATIVE ANALYSIS OF GREY-WOLF, ANTLION AND BACTERIAL COLONY OPTIMIZATION TECHNIQUES

Abstract

The present work highlights a comparative, data-driven assessment of three nature-inspired meta-heuristic optimization methods—Grey Wolf Optimization (GWO), Ant Lion Optimization (ALO), and Bacterial Colony Optimization (BCO in minimizing power consumption through optimal cluster formation and selection of cluster-heads (CH) for a VANET system. Simulation study shows that clustering can decrease total network power consumption by 80% as compared to without clustering. BCO results in the lowest power consumption, quicker convergence towards global optima, and more compact clustering structures, especially in dense environment. This study shows BCO as an energy-efficient optimization approach for clustering and routing in VANETs.