An Energy and Mobility-Aware Routing Protocol for FANET using Clustering-Based Intelligence

Abstract

Flying Adhoc Networks (FANETs), otherwise called as Unmanned Aerial Vehicles (UAVs) have arisen in different practices as of late. The quick development of UAVs causes unfortunate connection unwavering quality and information transmission effectiveness. To handel this issue, many clustering protocols have been developed. Among them, an Energy and Mobility-Aware Stable and Safe clustering (EMASS) protocol guarantees robustness and reliability in FANETs by allowing dynamic data transmission. But, it broadcasts hello messages regularly to maintain the routing path, resulting in high bandwidth and energy utilization. In this context, it is crucial to adjust the hello message interval and avoid redundant hello messages in high- mobility FANETs so that an Intelligent-based Energy and Mobility-aware Clustering (IEMC) protocol is proposed in this article. First, a novel bio-inspired process named Battle Royale Optimization (BRO) is introduced for cluster creation and Cluster Head (CH) selection processes. Then, a Deep Q- Learning (DQL)-based fast dynamic hello interval algorithm is developed to fine-tune the hello message interval and provide an energy-efficient solution for path maintenance. The DQL algorithm determines the hello interval by using data about allowed flying zones, the number of UAVs, communication, and speed range to adapt to rapid topological alterations. Using this protocol, both bandwidth and energy utilization are minimized. Finally, the simulation results illustrated that the IEMC protocol achieves greater network performance in contrast withthe existing clustering protocols for FANETs.