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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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    1. Zio, E. & Golea, L.R. & Rocco S., C.M., 2012. "Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 172-177.
    2. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    3. Zhang, Pengcheng & Peeta, Srinivas, 2011. "A generalized modeling framework to analyze interdependencies among infrastructure systems," Transportation Research Part B: Methodological, Elsevier, vol. 45(3), pages 553-579, March.
    4. Hosseini, Seyedmohsen & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "A review of definitions and measures of system resilience," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 47-61.
    5. Hong, Liu & Ouyang, Min & Peeta, Srinivas & He, Xiaozheng & Yan, Yongze, 2015. "Vulnerability assessment and mitigation for the Chinese railway system under floods," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 58-68.
    6. Hafiz Abdur Rahman & José R. Martí & K.D. Srivastava, 2011. "A hybrid systems model to simulate cyber interdependencies between critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 7(4), pages 265-288.
    7. Nicholson, Charles D. & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "Flow-based vulnerability measures for network component importance: Experimentation with preparedness planning," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 62-73.
    8. Zhang, Wenping & Xia, Yongxiang & Ouyang, Bo & Jiang, Lurong, 2015. "Effect of network size on robustness of interconnected networks under targeted attack," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 435(C), pages 80-88.
    9. Hernandez-Fajardo, Isaac & Dueñas-Osorio, Leonardo, 2013. "Probabilistic study of cascading failures in complex interdependent lifeline systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 260-272.
    10. Sergey V. Buldyrev & Roni Parshani & Gerald Paul & H. Eugene Stanley & Shlomo Havlin, 2010. "Catastrophic cascade of failures in interdependent networks," Nature, Nature, vol. 464(7291), pages 1025-1028, April.
    11. Johansson, Jonas & Hassel, Henrik, 2010. "An approach for modelling interdependent infrastructures in the context of vulnerability analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1335-1344.
    12. Ouyang, Min, 2016. "Critical location identification and vulnerability analysis of interdependent infrastructure systems under spatially localized attacks," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 106-116.
    13. Wang, Shuliang & Hong, Liu & Chen, Xueguang, 2012. "Vulnerability analysis of interdependent infrastructure systems: A methodological framework," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3323-3335.
    14. Chopade, Pravin & Bikdash, Marwan, 2016. "New centrality measures for assessing smart grid vulnerabilities and predicting brownouts and blackouts," International Journal of Critical Infrastructure Protection, Elsevier, vol. 12(C), pages 29-45.
    15. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    16. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
    17. Tony H. Grubesic & Timothy C. Matisziw & Alan T. Murray & Diane Snediker, 2008. "Comparative Approaches for Assessing Network Vulnerability," International Regional Science Review, , vol. 31(1), pages 88-112, January.
    18. Nan, Cen & Eusgeld, Irene & Kröger, Wolfgang, 2013. "Analyzing vulnerabilities between SCADA system and SUC due to interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 76-93.
    19. Sullivan, J.L. & Novak, D.C. & Aultman-Hall, L. & Scott, D.M., 2010. "Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 323-336, June.
    20. La Rovere, Stefano & Vestrucci, Paolo, 2012. "Investigation of the structure of a networked system," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 214-223.
    21. Rueda, Diego F. & Calle, Eusebi, 2017. "Using interdependency matrices to mitigate targeted attacks on interdependent networks: A case study involving a power grid and backbone telecommunications networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 16(C), pages 3-12.
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    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.

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