Survivability Analysis of Unmanned Aerial Vehicle Network based on Dynamic Weighted Clustering Algorithm with Dual Cluster Heads

Abstract

The unmanned aerial vehicles (UAVs) network is vulnerable due to the high mobility and energy-constrained characteristics of UAVs. Nonetheless, as a UAV-based communication network, a stable network topology is crucial for efficient communication. To this end, in this paper, we propose a dynamic weighted clustering algorithm with dual cluster heads (DWCA-DCH) in this paper to deploy the UAV network. To trade off communication efficiency and lifetime, the selection of prime and backup cluster heads is designed by synthetically considering communication quality and remaining energy of the UAV. Furthermore, a survivability analysis method based on Markov process (SAM-MP) is constructed to analyze the survivability performance of the proposed UAV network based on DWCA-DCH when the UAV node suffers from energy exhausting or accidents. The simulation results show that the survivability and stability of the UAV cluster ad hoc network based on DWCA-DCH proposed in this paper is improved by about 35% compared with the single cluster head network.