A Fast Weighted Clustering Algorithm for FANET

Multiple UAVs working in groups can significantly improve the efficiency in many applications. However, how to group the UAVs adaptively is an non-easy task due to the time-varying environments and tasks requirements. This paper investigates the clustering problem in flying ad hoc network (FANET). To enhance clustering efficiency and ensure rationality and reliability of the clustering structure, we propose a Fast Weighted Clustering Algorithm (FWCA) for node management in FANET. Specifically, we utilize various factors, including remaining energy, ideal node degree difference, node mobility, and link expiration time (LET) to elect cluster heads (CHs). Then, a node clustering mechanism is proposed, including the CH election, clustering process and cluster maintenance. Simulation results demonstrate that the proposed algorithm outperforms the benchmark schemes by reducing the number of CHs and clustering delay, while achieving relatively stable clustering results.