UAV Communication in FANETs with Metaheuristic Techniques

Abstract

The recent advancement in communication technologies has paved the way for the flying ad hoc networks (FANETs) by enabling the deployment of small UAVs unmanned aerial vehicles (UAVs). Owing to its potential features, FANETs have a wide variety of applications. However, the UAVs face certain restrictions in terms of their battery power and mobility, resulting in short lifetime and unreliable routing. In this paper, we try to primarily address the issue plaguing to the short lifetime of the FANETs, namely the limited power availability of the UAVs. The paper aims to minimize the energy consumption with the aid of a clustering scheme and observe its impact on the lifetime of the network. Two different clustering methods are employed to achieve this, and a comparative analysis based on its performances is presented. The first scheme implemented is the combination of the k-means clustering algorithm and the firefly algorithm while the second method is based on the glowworm swarm optimization (GSO) and the firefly algorithm. The primary clusters are formed with the k-means clustering and the GSO, respectively, while the firefly algorithm elects the cluster heads and derives the optimal positions of the UAVs in the cluster. The performance of the schemes is further compared in terms of the cluster building time and energy consumption.