A Quality Evaluation Method for Drone Swarm Command and Control Networks Based on Complex Network

To address the issues of structural diversity, modeling complexity, and the lack of evaluation methods in drone swarm command and control (C2) networks, this paper proposes a complex network-based quality evaluation method for drone swarm C2 networks from a network topology perspective. First, by analyzing the structure of the drone swarm C2 system, three hierarchical C2 network models are constructed, which are based on the Leader–Follower architecture, BA scale-free network, and ER random network, respectively. Subsequently, a drone swarm network quality evaluation indicator, system integrating network connectivity, load status, and transmission efficiency is established, along with an evaluation model that considers both static and dynamic characteristics. Finally, an analysis is conducted using networks of the same scale but different C2 structures. The evaluation results demonstrate that this method can effectively distinguish the performance of networks with different structures and exhibits good applicability under both random and targeted attack scenarios. Under static scenarios, distributed C2 networks exhibit the highest quality values, while centralized networks demonstrate the lowest. In random attack scenarios, the Leader–Follower structure achieves the highest network quality among the three hierarchical architectures, outperforming BA and ER network structures by 117% and 25%. In targeted attack scenarios, the ER network structure achieves the highest network quality, surpassing Leader–Follower and BA network structures by 66% and 17%. It provides a quantitative reference for the design and optimisation of the drone swarm C2 system structure.