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Criticality assessment of urban interdependent lifeline systems using a biased PageRank algorithm and a multilayer weighted directed network model

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  • Zhao, Chen
  • Li, Nan
  • Fang, Dongping

Abstract

Urban lifeline systems play vital roles in sustaining fundamental functionalities in urban areas. These systems, working collaboratively and synergistically, form a complex system of systems, in which disruptions in one system can rapidly propagate to others, posing a great challenge for the identification and protection of critical infrastructure facilities. This study introduces a new criticality assessment approach of interdependent lifeline systems. Given a weighted directed network of infrastructure systems, the proposed approach calculates vertex criticality through the biased PageRank algorithm: compared with the original PageRank algorithm, the biased one utilizes a personalization vector (in this context, vertex functional importance) in the process of criticality measurement. This algorithm design fulfils an integration of both network topology and function, and can comprehensively measure vertex criticality. To consider the impact of cascading failure, this criticality assessment method also adopts a linear combination form to take into account the criticality of child vertices using conditional probabilities as parameters. A case study is conducted on five real lifeline systems in a middle-sized county in China with over 300,000 inhabitants. Based on the case study model, targeted vertex attacks are carried out to illustrate the validity and effectiveness of this criticality measurement. Examining both network topological and function response, resulting curves show that the criticality ranking calculated with the proposed approach is better to reflect component topological and functional importance compared to other commonly used metrics. The main contribution of this study to the body of knowledge is the proposition of a new approach for criticality assessment of facilities in interdependent infrastructure systems under disaster scenarios, which provides a useful and intuitive guide for decision making process with regards to pre-disaster infrastructure protection.

Suggested Citation

  • Zhao, Chen & Li, Nan & Fang, Dongping, 2018. "Criticality assessment of urban interdependent lifeline systems using a biased PageRank algorithm and a multilayer weighted directed network model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 100-112.
    • Handle: RePEc:eee:ijocip:v:22:y:2018:i:c:p:100-112
    DOI: 10.1016/j.ijcip.2018.06.002
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    Cited by:

    1. Hai-xiang Guo & Xin-yu He & Xin-biao Lv & Yang Wu, 2024. "Risk analysis of rainstorm-urban lifeline system disaster chain based on the PageRank-risk matrix and complex network," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(12), pages 10583-10606, September.
    2. Quan Mao & Yuechen Liu, 2024. "Post-Disaster Performance and Restoration Sequences of Interdependent Critical Infrastructure Systems Considering Various Socioeconomic Impacts," Sustainability, MDPI, vol. 16(15), pages 1-18, August.
    3. Zhou, Shenghua & Yang, Yifan & Ng, S. Thomas & Xu, J. Frank & Li, Dezhi, 2020. "Integrating data-driven and physics-based approaches to characterize failures of interdependent infrastructures," International Journal of Critical Infrastructure Protection, Elsevier, vol. 31(C).

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