Cross-Layer and Energy-Aware AODV Routing Protocol for Flying Ad-Hoc Networks

Abstract

In recent years, unmanned aerial vehicles (UAVs) have become the trend for different types of research and applications. UAVs can accomplish some technical and risky tasks while still being safe, mobile, and inexpensive to operate. However, UAVs need flying ad-hoc networks (FANET) to operate in inaccessible or infrastructure-less areas. Subsequently, in many military and civil applications, the UAVs are connected ad hoc. FANET-based UAV systems have been developed for search and rescue, wildlife surveys, real-time monitoring, and delivery services. Maintaining the reliability and connectivity among UAV nodes in FANET becomes challenging because of the UAV movement, environmental conditions, energy efficiency, etc. Energy-aware routing protocols have become essential for developing advanced and effective FANETs. This paper presents a proposed Cross-Layer and Energy-Aware Ad-hoc On-demand Distance Vector (CLEA-AODV) routing protocol for improving FANET performance. The CLEA-AODV protocol is mainly divided into three sections: routing with AODV protocol, Glow Swarm Optimization (GSO)-based Cluster Head Selection, and Cooperative Medium Access Control (MAC). The cross-layer approach is implemented on the network layer and the data layer. The major parameters considered to evaluate the performance of the FANET are Packet Success Rate (PSR), Throughput (TP), End-to-End (E2E) delay, and packet drop ratio (PDR). The Network Simulator version 2 (NS2) is used to implement the CLEA-AODV protocol and evaluate the network performance. The results are compared with the standard AODV, Self-Organization Clustering-GSO (SOC-GSO), and Energy Efficient Neuro-Fuzzy Cluster-based Topology Construction with Meta-Heuristic Route Planning (EENFC-MRP) protocols. The results show that the CLEA-AODV surpasses these protocols in terms of PSR, TP, E2E delay, and PDR.