Experimental Analysis of ACO with Modified Firefly and Modified Genetic Algorithm for Routing in FANETs

The paper presents the performance evaluation of Nature-Inspired algorithms (NIA) namely Ant Colony Optimization (ACO) with newly implemented modified Firefly algorithm (MFA) and modified Genetic algorithm (MGA) for routing in Flying ad-hoc network (FANET). The use of NIA in FANET is required because FANET has quite different characteristics than that of other ad-hoc networks. The major area of concern in FANET is routing and no efficient routing algorithm has been developed for this issue. NIA is an optimization algorithm which process on the basis of nature of animals. NIA is divided into swarm based and evolutionary algorithm. This paper performs the evaluation and comparison of swarm-based algorithms and evolutionary algorithm on the performance parameters like successful packet delivery, end-to-end delay, overhead and throughput. As per the simulation results, MFA outperforms ACO and is the most efficient algorithm with MGA being the least efficient one.