@article{Sun2026, 
author = {Lijian Sun and Yun Zhou and Chao Chen},
title = {An active resilience planning method for C2 kill-webs based on hypergraphs and dynamic resilience potential},
year = {2026},
journal = {C2 Science and Technology},
keywords = {command and control, kill-web, hypergraph, resilience planning, information timeliness},
url = {https://www.sciopen.com/article/10.26599/C2ST.2026.9700004},
doi = {10.26599/C2ST.2026.9700004},
abstract = {The kill-web enhances the survivability and mission completion capability of combat systems through networked redundancy and adaptive organization. However, existing resilience metrics for command and control (C2) structures still rely on passive reaction paradigms, failing to capture the multi-path redundancy and active regulation requirements of kill-webs. This paper proposes an active resilience planning method for C2 kill-webs based on hypergraph modeling and dynamic resilience potential. First, the C2 kill-web is modeled as a directed hypergraph, where hyperedges are defined as combinations of functional units that collaboratively accomplish the same kill task. Hypergraph node centrality (cut-vertex betweenness and uniqueness factor) is proposed to quantify structural redundancy. Second, a dynamic resilience potential (DRP) function is constructed, integrating load margin, alternative path diversity, and historical overload risk, enabling real-time perception of vulnerable regions. Third, an adaptive early warning mechanism using exponentially weighted moving average-cumulative sum (EWMA-CUSUM) statistical process control is implemented, along with a risk-penalized load pre-migration mechanism. Finally, information timeliness is introduced as a complementary resilience dimension, yielding a resilience-AoI joint metric (RAJM). Simulations show that active resilience planning (ARP) improves the RAJM integral by 45%–86% over static and passive methods, and provides approximately 20 s of early warning. Overall, this work offers a systematic framework for resilient C2 organizational structures aligned with the JADC2 vision.}
}