Self-organization based clustering scheme for FANETs using Glowworm Swarm Optimization

As UAVs in a Flying ad-hoc Network (FANET) are mobile in nature, thus results in frequently changing topology and creates the communication issues. For better networking to have efficient communication in FANETs, we propose self-organization based clustering scheme inspired by the behavioral study of glowworm swarm optimization (GSO) for cluster formation and management. The cluster head election and cluster formation take place based on connectivity with the ground control station along with luciferin value and residual energy of the UAVs. The cluster management mechanism uses behavioral study of GSO by updating the luciferin value based on the UAVs’ position. Furthermore we propose a mechanism for route selection based on the neighbor range, residual energy and position of UAV for efficient communication. The performance of the proposed SOCS is evaluated in terms of energy consumption, cluster building time, cluster lifetime and probability of delivery success with other existing bio-inspired clustering schemes.