A Mobility Aware Clustering Scheme Based on Swarm Intelligence in FANETs

Abstract

The emerging Flying ad-hoc Network (FANET) has been used in many applications and services ranging from military to emergency rescue. Unmanned Aerial Vehicle (UAV) clustering is a significant technology in FANETs. In each cluster, the cluster head (CH) is responsible for cluster management. However, due to the frequent movement and limited energy of UAVs, one of the foremost challenges in FANETs is unstable communication performance of cluster. Hence, to cope with this issue, we propose a Mobility Aware Clustering scheme based on Swarm Intelligence (MACSI) for FANETs, which is enlightened by animal collective behavior. More specifically, the modified glowworm swarm optimization (GSO) algorithm based on chaos strategy is put forward for CH selection and cluster formation. It aims to help UAVs cooperate with each other to conduct missions and change their positions accordingly. In addition, a stable CH selection mechanism depends on energy, position and the movement relationship. Our proposal has been evaluated with respect to metrics as energy consumption and cluster life time. The experimental results obtained validate that, the proposed scheme has less energy consumption and extended cluster life time compared with existing clustering schemes.