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System-of-Systems Resilience Analysis and Design Using Bayesian and Dynamic Bayesian Networks

Author

Listed:
  • Tianci Jiao

    (College of Computer, National University of Defense Technology, Changsha 410075, China)

  • Hao Yuan

    (College of System Engineering, National University of Defense Technology, Changsha 410075, China)

  • Jing Wang

    (College of Computer, National University of Defense Technology, Changsha 410075, China)

  • Jun Ma

    (College of Computer, National University of Defense Technology, Changsha 410075, China)

  • Xiaoling Li

    (College of Computer, National University of Defense Technology, Changsha 410075, China)

  • Aimin Luo

    (College of System Engineering, National University of Defense Technology, Changsha 410075, China)

Abstract

A System-of-Systems (SoS) is characterized both by independence and by inter-dependency. This inter-dependency, while allowing an SoS to achieve its objectives, also means that failures can cascade throughout the SoS. An SoS needs to be resilient to deal with the impact of complex internal and external environments. In this paper, we propose a resilience analysis method of an SoS based on a hierarchy structure. Firstly, we establish a hierarchy structure, which is ranked from high to low as capability level, activity level and system level. Then, Bayesian Networks (BNs) and Dynamic Bayesian Networks (DBNs) are used to analyze the resilience of the SoS. A resilience-based system importance metric is introduced, which is used in the budget allocation optimization problem during the development domain of an SoS. This paper proposes a mathematical programming model aimed at optimizing SoS resilience by optimally using budget to the subsystem. The application of the proposed approach is demonstrated using a case study: a Next Generation Air Transportation setting. The study results provide evidence that the proposed inter-dependency analysis based on Bayesian theory and the SoS resilience design approach can assist SoS system engineers in increasing expected SoS resilience during the development domain.

Suggested Citation

  • Tianci Jiao & Hao Yuan & Jing Wang & Jun Ma & Xiaoling Li & Aimin Luo, 2024. "System-of-Systems Resilience Analysis and Design Using Bayesian and Dynamic Bayesian Networks," Mathematics, MDPI, vol. 12(16), pages 1-22, August.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:16:p:2510-:d:1456160
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    References listed on IDEAS

    as
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