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Reliability analysis of network systems subject to probabilistic propagation failures and failure isolation effects

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  • Peng Su
  • Guanjun Wang

Abstract

In this article, the reliability of network systems subject to probabilistic propagation failure and failure isolation effects is considered. Probabilistic propagation failure is the failure of some components in a system, which will cause other components to fail with certain probabilities. Probabilistic propagation failure exists in various network systems, such as computing network system and nuclear power generating network system. Failure isolation means that the failure of a trigger component will lead to its corresponding dependent components being isolated from the network system. Since the failure isolation effect is activated only when the failure of trigger components occurs before the occurrence of probabilistic propagation failure, there exists a competing failure in the time domain between the failure of a trigger component and the components with probabilistic propagation failure effect. If a trigger component failure occurs first, the system is insensitive to any failures of components being isolated. In this article, a combinatorial method based on binary decision diagram is proposed to analyze the reliability of the network systems subject to probabilistic propagation failure and failure isolation effects. The method can be applied to any network system and any type of lifetime distribution of the system components. As an example, a wide area network system is analyzed. Some numerical results about reliability indexes are provided to verify the feasibility and accuracy of the proposed method.

Suggested Citation

  • Peng Su & Guanjun Wang, 2022. "Reliability analysis of network systems subject to probabilistic propagation failures and failure isolation effects," Journal of Risk and Reliability, , vol. 236(2), pages 290-306, April.
  • Handle: RePEc:sae:risrel:v:236:y:2022:i:2:p:290-306
    DOI: 10.1177/1748006X19893547
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    References listed on IDEAS

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    Cited by:

    1. Lirong Cui & David W Coit, 2022. "Guest Editorial: SMRLO-2019 Special Issue," Journal of Risk and Reliability, , vol. 236(2), pages 223-224, April.

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