IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v8y2015i10p12187-12210d57834.html
   My bibliography  Save this article

Recent Progress on the Resilience of Complex Networks

Author

Listed:
  • Jianxi Gao

    (Center for Complex Network Research and Department of Physics, Northeastern University, Boston, MA 02115, USA)

  • Xueming Liu

    (Key Laboratory of Image Information Processing and Intelligent Control, School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China
    Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA)

  • Daqing Li

    (School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
    Science and Technology on Reliability and Environmental Engineering Laboratory, Beijing 100191, China)

  • Shlomo Havlin

    (Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel)

Abstract

Many complex systems in the real world can be modeled as complex networks, which has captured in recent years enormous attention from researchers of diverse fields ranging from natural sciences to engineering. The extinction of species in ecosystems and the blackouts of power girds in engineering exhibit the vulnerability of complex networks, investigated by empirical data and analyzed by theoretical models. For studying the resilience of complex networks, three main factors should be focused on: the network structure, the network dynamics and the failure mechanism. In this review, we will introduce recent progress on the resilience of complex networks based on these three aspects. For the network structure, increasing evidence shows that biological and ecological networks are coupled with each other and that diverse critical infrastructures interact with each other, triggering a new research hotspot of “networks of networks” (NON), where a network is formed by interdependent or interconnected networks. The resilience of complex networks is deeply influenced by its interdependence with other networks, which can be analyzed and predicted by percolation theory. This review paper shows that the analytic framework for Energies 2015, 8 12188 NON yields novel percolation laws for n interdependent networks and also shows that the percolation theory of a single network studied extensively in physics and mathematics in the last 60 years is a specific limited case of the more general case of n interacting networks. Due to spatial constraints inherent in critical infrastructures, including the power gird, we also review the progress on the study of spatially-embedded interdependent networks, exhibiting extreme vulnerabilities compared to their non-embedded counterparts, especially in the case of localized attack. For the network dynamics, we illustrate the percolation framework and methods using an example of a real transportation system, where the analysis based on network dynamics is significantly different from the structural static analysis. For the failure mechanism, we here review recent progress on the spontaneous recovery after network collapse. These findings can help us to understand, realize and hopefully mitigate the increasing risk in the resilience of complex networks.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:12187-12210:d:57834
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/8/10/12187/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/8/10/12187/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dorogovtsev, S.N. & Mendes, J.F.F., 2003. "Evolution of Networks: From Biological Nets to the Internet and WWW," OUP Catalogue, Oxford University Press, number 9780198515906.
    2. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    3. Olivier J. Blanchard & Lawrence H. Summers, 1986. "Hysteresis and the European Unemployment Problem," NBER Chapters, in: NBER Macroeconomics Annual 1986, Volume 1, pages 15-90, National Bureau of Economic Research, Inc.
    4. Ash, J. & Newth, D., 2007. "Optimizing complex networks for resilience against cascading failure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 380(C), pages 673-683.
    5. Blanchard, Olivier J. & Summers, Lawrence H., 1987. "Hysteresis in unemployment," European Economic Review, Elsevier, vol. 31(1-2), pages 288-295.
    6. Chaoming Song & Shlomo Havlin & Hernán A. Makse, 2005. "Self-similarity of complex networks," Nature, Nature, vol. 433(7024), pages 392-395, January.
    7. Wei Zou & D. V. Senthilkumar & Raphael Nagao & István Z. Kiss & Yang Tang & Aneta Koseska & Jinqiao Duan & Jürgen Kurths, 2015. "Restoration of rhythmicity in diffusively coupled dynamical networks," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
    8. Benoit Robert & Luciano Morabito, 2008. "The operational tools for managing physical interdependencies among critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 4(4), pages 353-367.
    9. He, Zhiwei & Liu, Shuai & Zhan, Meng, 2013. "Dynamical robustness analysis of weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4181-4191.
    10. Amir Bashan & Ronny P. Bartsch & Jan. W. Kantelhardt & Shlomo Havlin & Plamen Ch. Ivanov, 2012. "Network physiology reveals relations between network topology and physiological function," Nature Communications, Nature, vol. 3(1), pages 1-9, January.
    11. 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.
    12. Jin-Hua Zhao & Hai-Jun Zhou & Yang-Yu Liu, 2013. "Inducing effect on the percolation transition in complex networks," Nature Communications, Nature, vol. 4(1), pages 1-6, December.
    13. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    14. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    15. Matthew O. Jackson & Brian W. Rogers, 2007. "Meeting Strangers and Friends of Friends: How Random Are Social Networks?," American Economic Review, American Economic Association, vol. 97(3), pages 890-915, June.
    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. Havlin, Shlomo & Stanley, H. Eugene & Bashan, Amir & Gao, Jianxi & Kenett, Dror Y., 2015. "Percolation of interdependent network of networks," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 4-19.
    2. Yao, Jialing & Sun, Bingbin & Xi, lifeng, 2019. "Fractality of evolving self-similar networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 211-216.
    3. Zhu, Qian & Zhu, Zhiliang & Wang, Yifan & Yu, Hai, 2016. "Fuzzy-information-based robustness of interconnected networks against attacks and failures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 194-203.
    4. Lu, Qing-Chang & Xu, Peng-Cheng & Zhao, Xiangmo & Zhang, Lei & Li, Xiaoling & Cui, Xin, 2022. "Measuring network interdependency between dependent networks: A supply-demand-based approach," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    5. Selen Onel & Abe Zeid & Sagar Kamarthi, 2011. "The structure and analysis of nanotechnology co-author and citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 119-138, October.
    6. 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.
    7. Jalili, Mahdi, 2011. "Error and attack tolerance of small-worldness in complex networks," Journal of Informetrics, Elsevier, vol. 5(3), pages 422-430.
    8. Nie, Tingyuan & Fan, Bo & Wang, Zhenhao, 2022. "Complexity and robustness of weighted circuit network of placement," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    9. Kashyap, G. & Ambika, G., 2019. "Link deletion in directed complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 631-643.
    10. Vitor H. P. Louzada & Fabio Daolio & Hans J. Herrmann & Marco Tomassini, "undated". "Smart rewiring for network robustness," Working Papers ETH-RC-14-004, ETH Zurich, Chair of Systems Design.
    11. Ou, Ruiqiu & Yang, Jianmei, 2012. "On structural properties of scale-free networks with finite size," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 887-894.
    12. Daniel Miehle & Björn Häckel & Stefan Pfosser & Jochen Übelhör, 2020. "Modeling IT Availability Risks in Smart Factories," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(4), pages 323-345, August.
    13. Zhang, Xue-Jun & Xu, Guo-Qiang & Zhu, Yan-Bo & Xia, Yong-Xiang, 2016. "Cascade-robustness optimization of coupling preference in interconnected networks," Chaos, Solitons & Fractals, Elsevier, vol. 92(C), pages 123-129.
    14. Zhou, Hong-Li & Zhang, Xiao-Dong, 2018. "Dynamic robustness of knowledge collaboration network of open source product development community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 601-612.
    15. Dror Kenett & Shlomo Havlin, 2015. "Network science: a useful tool in economics and finance," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 14(2), pages 155-167, November.
    16. Peng, Xingzhao & Yao, Hong & Du, Jun & Wang, Zhe & Ding, Chao, 2015. "Invulnerability of scale-free network against critical node failures based on a renewed cascading failure model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 69-77.
    17. 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.
    18. Kong, Linghao & Wang, Lizhi & Cao, Zhongzheng & Wang, Xiaohong, 2024. "Resilience evaluation of UAV swarm considering resource supplementation," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    19. G. De Masi & M. Gallegati, 2012. "Bank–firms topology in Italy," Empirical Economics, Springer, vol. 43(2), pages 851-866, October.
    20. 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.

    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:jeners:v:8:y:2015:i:10:p:12187-12210:d:57834. 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.