IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i3p1202-d317785.html
   My bibliography  Save this article

Influence of Interlink Topology on Multilayer Network Robustness

Author

Listed:
  • Fang Zhou

    (College of Information and Management Science, Henan Agricultural University, Zhengzhou 450046, China)

  • Xiang He

    (Department of Construction Management, Dalian University of Technology, Dalian 116024, China)

  • Yongbo Yuan

    (Department of Construction Management, Dalian University of Technology, Dalian 116024, China)

  • Mingyuan Zhang

    (Department of Construction Management, Dalian University of Technology, Dalian 116024, China)

Abstract

Cascading failures between interdependent multilayer networks are being widely studied, especially the trend of robustness caused by the interlinks between networks. However, few researchers pay attention to the effect of the interlink topology on the robustness of coupled networks, which is a critical interlink factor of multilayer networks. In this study, the method frame of multilayer network experiment simulation is given. Through numerical simulation and actual network simulation, the exhaustive method is used to enumerate all the patterns of interlink topological relations of multilayer networks (three-layer or more). The research verifies that the interlink topology affects the global robustness and that there exists a fragile interlink pattern in the patterns of interlink topologies. The star-like interlink pattern with the most uneven interlink-degree distribution leads to the weakest robustness; the pattern with average interlink-degree distribution reveals good global stability as a loop-like pattern or entire interlink pattern. In addition, the influence of interlink topology is independent. The simulation results are not affected by the network layer number and intraparameters (including the network-generated form, each layer of network node number, and average degree of each layer of network). Thus, ignoring the interlink topology may result in the actual system suddenly becoming vulnerable before the theoretical calculation point. Interlink topology as an independent factor affecting the robustness of multilayer networks should be paid more attention.

Suggested Citation

  • Fang Zhou & Xiang He & Yongbo Yuan & Mingyuan Zhang, 2020. "Influence of Interlink Topology on Multilayer Network Robustness," Sustainability, MDPI, vol. 12(3), pages 1-19, February.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:1202-:d:317785
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/3/1202/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/3/1202/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jianwei & Jiang, Chen & Qian, Jianfei, 2014. "Robustness of interdependent networks with different link patterns against cascading failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 535-541.
    2. 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.
    3. Cui, Pengshuai & Zhu, Peidong & Wang, Ke & Xun, Peng & Xia, Zhuoqun, 2018. "Enhancing robustness of interdependent network by adding connectivity and dependence links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 185-197.
    4. Alessandro Vespignani, 2010. "The fragility of interdependency," Nature, Nature, vol. 464(7291), pages 984-985, April.
    5. Gao, Yan-Li & Chen, Shi-Ming & Nie, Sen & Ma, Fei & Guan, Jun-Jie, 2018. "Robustness analysis of interdependent networks under multiple-attacking strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 495-504.
    6. Cheng, Zunshui & Cao, Jinde, 2015. "Cascade of failures in interdependent networks coupled by different type networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 193-200.
    7. Li, Daqing & Zhang, Qiong & Zio, Enrico & Havlin, Shlomo & Kang, Rui, 2015. "Network reliability analysis based on percolation theory," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 556-562.
    8. Dong, Gaogao & Du, Ruijin & Tian, Lixin & Liu, Runran, 2015. "Robustness of network of networks with interdependent and interconnected links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 11-18.
    9. 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.
    10. Jianxi Gao & Xueming Liu & Daqing Li & Shlomo Havlin, 2015. "Recent Progress on the Resilience of Complex Networks," Energies, MDPI, vol. 8(10), pages 1-24, October.
    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. Fang Zhou & Yanchao Du & Yongbo Yuan & Mingyuan Zhang, 2019. "The cross-networks impact analysis and assessment in multilayer interdependent networks: A case study of critical infrastructures," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(07), pages 1-13, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Shangjia & Wang, Haizhong & Mostafizi, Alireza & Song, Xuan, 2020. "A network-of-networks percolation analysis of cascading failures in spatially co-located road-sewer infrastructure networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    2. Gao, Xingle & Peng, Minfang & Tse, Chi K., 2022. "Robustness analysis of cyber-coupled power systems with considerations of interdependence of structures, operations and dynamic behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
    3. Ji, Xingpei & Wang, Bo & Liu, Dichen & Dong, Zhaoyang & Chen, Guo & Zhu, Zhenshan & Zhu, Xuedong & Wang, Xunting, 2016. "Will electrical cyber–physical interdependent networks undergo first-order transition under random attacks?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 235-245.
    4. Kai Gong & Jia-Jian Wu & Ying Liu & Qing Li & Run-Ran Liu & Ming Tang, 2019. "The Effective Healing Strategy against Localized Attacks on Interdependent Spatially Embedded Networks," Complexity, Hindawi, vol. 2019, pages 1-10, May.
    5. Cui, Pengshuai & Zhu, Peidong & Shao, Chengcheng & Xun, Peng, 2017. "Cascading failures in interdependent networks due to insufficient received support capability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 777-788.
    6. Shen, Yi & Ren, Gang & Zhang, Ning & Song, Guohao & Wang, Qin & Ran, Bin, 2020. "Effects of mutual traffic redistribution on robustness of interdependent networks to cascading failures under fluctuant load," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    7. Cui, Pengshuai & Zhu, Peidong & Wang, Ke & Xun, Peng & Xia, Zhuoqun, 2018. "Enhancing robustness of interdependent network by adding connectivity and dependence links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 185-197.
    8. Xia, Yongxiang & Zhang, Wenping & Zhang, Xuejun, 2016. "The effect of capacity redundancy disparity on the robustness of interconnected networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 561-568.
    9. Liu, Kai & Wang, Ming & Zhu, Weihua & Wu, Jinshan & Yan, Xiaoyong, 2018. "Vulnerability analysis of an urban gas pipeline network considering pipeline-road dependency," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 79-89.
    10. Zhang, Yanlu & Yang, Naiding, 2018. "Vulnerability analysis of interdependent R&D networks under risk cascading propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 1056-1068.
    11. Wang, Jianwei & Wang, Siyuan & Wang, Ziwei, 2022. "Robustness of spontaneous cascading dynamics driven by reachable area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    12. 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.
    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. Wang, Jianwei & Li, Yun & Zheng, Qiaofang, 2015. "Cascading load model in interdependent networks with coupled strength," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 242-253.
    15. Wang, Jianwei & Cai, Lin & Xu, Bo & Li, Peng & Sun, Enhui & Zhu, Zhiguo, 2016. "Out of control: Fluctuation of cascading dynamics in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1231-1243.
    16. Qing Cai & Mahardhika Pratama & Sameer Alam, 2019. "Interdependency and Vulnerability of Multipartite Networks under Target Node Attacks," Complexity, Hindawi, vol. 2019, pages 1-16, November.
    17. Zhao, Yanyan & Zhou, Jie & Zou, Yong & Guan, Shuguang & Gao, Yanli, 2022. "Characteristics of edge-based interdependent networks," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    18. Gao, Yan-Li & Chen, Shi-Ming & Nie, Sen & Ma, Fei & Guan, Jun-Jie, 2018. "Robustness analysis of interdependent networks under multiple-attacking strategies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 495-504.
    19. Wang, Jianwei & Sun, Enhui & Xu, Bo & Li, Peng & Ni, Chengzhang, 2016. "Abnormal cascading failure spreading on complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 695-701.
    20. Fauzan Hanif Jufri & Jun-Sung Kim & Jaesung Jung, 2017. "Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event," Energies, MDPI, vol. 10(11), pages 1-17, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:3:p:1202-:d:317785. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.