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A resilient network recovery framework against cascading failures with deep graph learning

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  • Jian Zhou
  • Weijian Zheng
  • Dali Wang
  • David W. Coit

Abstract

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. This work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

Suggested Citation

  • Jian Zhou & Weijian Zheng & Dali Wang & David W. Coit, 2024. "A resilient network recovery framework against cascading failures with deep graph learning," Journal of Risk and Reliability, , vol. 238(1), pages 193-203, February.
  • Handle: RePEc:sae:risrel:v:238:y:2024:i:1:p:193-203
    DOI: 10.1177/1748006X221128869
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    References listed on IDEAS

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    1. Sun, Lina & Huang, Ning & Li, Ruiying & Bai, Yanan, 2019. "A new fractal reliability model for networks with node fractal growth and no-loop," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 699-707.
    2. Lee, D.-S. & Goh, K.-I. & Kahng, B. & Kim, D., 2004. "Sandpile avalanche dynamics on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 84-91.
    3. Li, Ruiying & Gao, Ying, 2022. "On the component resilience importance measures for infrastructure systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 36(C).
    4. Almoghathawi, Yasser & Barker, Kash & Albert, Laura A., 2019. "Resilience-driven restoration model for interdependent infrastructure networks," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 12-23.
    5. Zhou, Jian & Coit, David W. & Felder, Frank A. & Wang, Dali, 2021. "Resiliency-based restoration optimization for dependent network systems against cascading failures," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    6. Volodymyr Mnih & Koray Kavukcuoglu & David Silver & Andrei A. Rusu & Joel Veness & Marc G. Bellemare & Alex Graves & Martin Riedmiller & Andreas K. Fidjeland & Georg Ostrovski & Stig Petersen & Charle, 2015. "Human-level control through deep reinforcement learning," Nature, Nature, vol. 518(7540), pages 529-533, February.
    7. Zhou, Jian & Huang, Ning & Coit, David W. & Felder, Frank A., 2018. "Combined effects of load dynamics and dependence clusters on cascading failures in network systems," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 116-126.
    8. Xu, Zhaoping & Ramirez-Marquez, Jose Emmanuel & Liu, Yu & Xiahou, Tangfan, 2020. "A new resilience-based component importance measure for multi-state networks," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    9. Benjamin Schäfer & Dirk Witthaut & Marc Timme & Vito Latora, 2018. "Author Correction: Dynamically induced cascading failures in power grids," Nature Communications, Nature, vol. 9(1), pages 1-1, December.
    10. Yasser Almoghathawi & Andrés D. González & Kash Barker, 2021. "Exploring Recovery Strategies for Optimal Interdependent Infrastructure Network Resilience," Networks and Spatial Economics, Springer, vol. 21(1), pages 229-260, March.
    11. Liu, Xing & Ferrario, Elisa & Zio, Enrico, 2019. "Identifying resilient-important elements in interdependent critical infrastructures by sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 423-434.
    12. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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    Cited by:

    1. Ning, Ru & Wang, Xiaoyue & Zhao, Xian & Li, Ziyue, 2024. "Joint optimization of preventive maintenance and triggering mechanism for k-out-of-n: F systems with protective devices based on periodic inspection," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    2. Liu, Jintao & Ji, Lin & Chen, Keyi & Li, Chenling & Duan, Huayu, 2025. "Railway operational hazard prediction and control based on knowledge graph embedding and topological analysis," Reliability Engineering and System Safety, Elsevier, vol. 258(C).

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