Performance evaluation of routing in flying ad-hoc networks using nature-inspired algorithms

Abstract

Flying ad-hoc network (FANET) has been growing rapidly and can utilized in sectors such as disaster response, healthcare, military, agriculture, and more. These networks utilize Unmanned aerial vehicles (UAVs), required advanced routing algorithms for effective communication. Due to the lack of suitable routing algorithms, FANETs often encounter communication issues. This article explores the integration of Nature-inspired based routing algorithms into the FANET framework. Specifically, it examines the two distinct algorithms namely, swarm intelligence and genetic algorithms. Simulated results demonstrate the superiority of the proposed algorithm over standard benchmark schemes. Validation of the proposed algorithm using performance parameters, such as throughput, reveals significant improvements over benchmark schemes. Moreover, the packet delivery ratio for providing resources to FANET users is 98% while achieving minimum end-to-end delay for the proposed scheme. These findings underscore the potential of Nature-inspired algorithms (NIAs) across various scenarios within the FANET framework.