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Link overlap, viability, and mutual percolation in multiplex networks

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  • Min, Byungjoon
  • Lee, Sangchul
  • Lee, Kyu-Min
  • Goh, K.-I.

Abstract

Many real-world complex systems are best modeled by multiplex networks. The multiplexity has proved to have broad impact on the system’s structure and function. Most theoretical studies on multiplex networks to date, however, have largely ignored the effect of the link overlap across layers despite strong empirical evidences for its significance. In this article, we investigate the effect of the link overlap in the viability of multiplex networks, both analytically and numerically. After a short recap of the original multiplex viability study, the distinctive role of overlapping links in viability and mutual connectivity is emphasized and exploited for setting up a proper analytic framework. A rich phase diagram for viability is obtained and greatly diversified patterns of hysteretic behavior in viability are observed in the presence of link overlap. Mutual percolation with link overlap is revisited as a limit of multiplex viability problem, and the controversy between existing results is clarified. The distinctive role of overlapping links is further demonstrated by the different responses of networks under random removals of overlapping and non-overlapping links, respectively, as well as under several link-removal strategies. Our results show that the link overlap facilitates the viability and mutual percolation; at the same time, the presence of link overlap poses a challenge in analytical approaches to the problem.

Suggested Citation

  • Min, Byungjoon & Lee, Sangchul & Lee, Kyu-Min & Goh, K.-I., 2015. "Link overlap, viability, and mutual percolation in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 72(C), pages 49-58.
  • Handle: RePEc:eee:chsofr:v:72:y:2015:i:c:p:49-58
    DOI: 10.1016/j.chaos.2014.12.016
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    References listed on IDEAS

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    1. 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.
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    Cited by:

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    2. Liang, Yuan & Qi, Mingze & Huangpeng, Qizi & Duan, Xiaojun, 2023. "Percolation of interlayer feature-correlated multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Shekhtman, Louis M. & Danziger, Michael M. & Havlin, Shlomo, 2016. "Recent advances on failure and recovery in networks of networks," Chaos, Solitons & Fractals, Elsevier, vol. 90(C), pages 28-36.
    4. Kyu-Min Lee & Kwang-Il Goh, 2016. "Strength of weak layers in cascading failures on multiplex networks: case of the international trade network," Papers 1603.05181, arXiv.org, revised May 2016.
    5. Baxter, G.J. & da Costa, R.A. & Dorogovtsev, S.N. & Mendes, J.F.F., 2022. "Weak percolation on multiplex networks with overlapping edges," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    6. Osat, Saeed & Radicchi, Filippo, 2018. "Observability transition in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 745-761.
    7. Gao, Bo & Deng, Zhenghong & Zhao, Dawei, 2016. "Competing spreading processes and immunization in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 175-181.
    8. Wang, Weihong & Chen, MingMing & Min, Yong & Jin, Xiaogang, 2016. "Structural diversity effects of multilayer networks on the threshold of interacting epidemics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 254-262.

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