Political Optimizer Based Robust Energy Aware Clustering Scheme for Flying Ad Hoc Networks

Unmanned Aerial Vehicles (UAVs) are broadly utilized in civilian and military fields with the continuous growth of (UAVs) technology. Multi-UAV networks were commonly termed as flying ad hoc networks (FANETs). Segregating numerous UAVs into clusters for management could enhance network scalability, minimize energy consumption, and maximize network lifetime to some extent, thus UAV clustering will be a crucial direction for drone network applications. But UAV have the features of high mobility and limited energy resources, which put forth difficulties in UAVs cluster transmission networking. Therefore, this article develops a Political Optimizer based Robust Energy Aware Clustering Scheme (PO-REACS) for FANET. The proposed PO-REACS technique aims to cluster UAVs for maximum network efficiency. In the presented PO-REACS technique, the major concepts of multi-staged procedure of politics in human society are used. For an effective selection of cluster heads (CHs), the PO-REACS technique computes multiple parameter fitness functions. For highlighting the superior performances of the PO-REACS system, a widespread simulation studies are made. The comparison study stated the betterment of the PO-REACS technique over existing methodologies.