Research on the Robustness of Command and Control Networks under Cascading Failures

The current analysis of cascading failures in command and control networks pays little attention to their roles and mechanisms, resulting in challenges in quantifying survivability evaluation metrics and limiting practical application. To address these issues, this paper designs a command and control network model with a recovery strategy to improve the scientific evaluation of critical nodes and enhance the reliability of subsequent cascading failure simulations. Two capacity parameters are introduced to analyze the nonlinear behavior between network node load and capacity, and an optimal recovery strategy is proposed. This strategy prioritizes the recovery of critical nodes, thereby minimizing the overall probability of network failure. Simulations were conducted under both random failure and deliberate attack scenarios, comparing the proposed strategy with random recovery and betweenness-priority recovery strategies to identify the optimal recovery approach. The experiments showed that the optimal recovery strategy significantly enhanced the network’s survivability and recovery efficiency, allowing for the restoration of basic network functions in the shortest possible time and reducing the impact of cascading failures. By integrating the operability and uncertainty of real-world command and control networks, this method improved the network’s recovery capability and overall stability in the face of cascading failures through scientific evaluation and strategy optimization.