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Research on resilience measurement and optimization of networked command information system

Author

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  • Zhong, Yun
  • Zhang, Yongzhuang
  • Zhang, Jieyong
  • Wan, Lujun

Abstract

In order to improve the ability of networked command information system to actively absorb disturbances, adapt to adjust and recover and regenerate after encountering risks, this study proposes a novel solution from the perspective of resilience measurement and optimization of functional chain logical relationship on the basis of system function decoupling. First of all, the networked command information system operational pattern and network characteristics are summarized, and the system resilience is analyzed, including the resilience elements (robustness element, recovery element, and responsiveness element) and motives, and the resilience process. Then, the system resilience was measured, and the resilience measurement results were generated based on the analysis of the factors affecting the resilience measurement. Finally, based on the resilience measurement results, system resilience optimization based on node backup, based on structural design, and based on node restoration are carried out, respectively. Through this study, some meaningful conclusions are obtained, which are conducive to guiding the operation and maintenance management of networked command information system.

Suggested Citation

  • Zhong, Yun & Zhang, Yongzhuang & Zhang, Jieyong & Wan, Lujun, 2025. "Research on resilience measurement and optimization of networked command information system," Reliability Engineering and System Safety, Elsevier, vol. 261(C).
    • Handle: RePEc:eee:reensy:v:261:y:2025:i:c:s0951832025002492
    DOI: 10.1016/j.ress.2025.111048
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    References listed on IDEAS

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    1. Yang, Bofan & Zhang, Lin & Zhang, Bo & Xiang, Yang & An, Lei & Wang, Wenfeng, 2022. "Complex equipment system resilience: Composition, measurement and element analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    2. Feng, Tianyu & He, Yihai & Shi, Rui & Li, Jiayang & Dai, Wei & Yu, Shuang, 2025. "Functional risk modeling and selective maintenance optimization approach for multi-stage manufacturing system considering operational robustness," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    3. O’Neil, Ryan & Diallo, Claver & Khatab, Abdelhakim & Rezg, Nidhal, 2025. "Enhancing critical network infrastructure resilience through optimal post-disruption maintenance and routing decisions," Reliability Engineering and System Safety, Elsevier, vol. 257(PA).
    4. Geng, Sunyue & Liu, Sifeng, 2025. "An agent-based framework for resilience analysis of service networks," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    5. Chen, Xin & Li, Jie, 2025. "A novel approach for structural system reliability evaluation using decoupled first-order reliability method and equivalent extreme-value event," Reliability Engineering and System Safety, Elsevier, vol. 257(PB).
    6. Per Olsson, 2022. "Measuring Quality of Military Equipment," Defence and Peace Economics, Taylor & Francis Journals, vol. 33(1), pages 93-107, January.
    7. Mishra, Sakshi & Anderson, Kate & Miller, Brian & Boyer, Kyle & Warren, Adam, 2020. "Microgrid resilience: A holistic approach for assessing threats, identifying vulnerabilities, and designing corresponding mitigation strategies," Applied Energy, Elsevier, vol. 264(C).
    8. Dui, Hongyan & Liu, Meng & Song, Jiaying & Wu, Shaomin, 2023. "Importance measure-based resilience management: Review, methodology and perspectives on maintenance," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
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    1. Zhang, Jingru & Zhang, Qin & Wu, Jun & Du, Junliang & Liu, Yu, 2026. "Optimizing redundancy of UAVs system by targeting risk-significant components for improved mission success probability," Reliability Engineering and System Safety, Elsevier, vol. 270(C).
    2. Wu, Bei & Wang, Wenhao & Tan, Zhizhong & Ding, Dong, 2025. "Resilience modeling for discrete-time multi-state systems based on aggregated Markov chains," Reliability Engineering and System Safety, Elsevier, vol. 264(PB).
    3. Gao, Chong & Jiang, Hui & Guo, Xiaoling, 2026. "Bridging interactions and robustness of inter-community structures in disaster response systems: A hypergraph-based analysis," Reliability Engineering and System Safety, Elsevier, vol. 266(PB).

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