A Robustness Optimization Method for UAV Swarm Communication Network Topology Based on Flocking Behavior

In complex battlefield environments where adversarial attacks are frequent and uncrewed aerial vehicle (UAV) swarms are vulnerable to interference, the communication topology is prone to damage. To ensure the mission success rate of UAV swarms, optimizing network robustness is particularly important. In this context, this article presents a study on enhancing the coordination capability of UAV swarms under enemy attacks and interference by implementing a zone-based isolation management method, a preventive optimization method based on a hierarchical simulated annealing (HSA) algorithm with small-world network characteristics, and a recovery optimization method based on a temporary leader mechanism. A communication topology model for UAV swarms is also established. The partitioned isolation management method divides the overall topology into multiple connected subtopologies, thereby limiting the impact of faults or attacks within a specific area. The HSA method based on small-world networks optimizes the network topology within interference regions, reducing internal links while maintaining overall connectivity. In addition, when the topology is damaged, temporary leaders are selected to maintain the integrity of the remaining topology. Simulation results indicate that the proposed preventive robustness optimization method can effectively enhance the robustness of the communication network. The recovery optimization method maintains the connectivity of the remaining swarm topology and enables the reestablishment of the flocking state, demonstrating the practical effectiveness of the proposed robustness optimization approaches.