Skip to main content
Log in

Catastrophic cascade of failures in interdependent networks

  • Letter
  • Published:

From Nature

View current issue Submit your manuscript

Abstract

Complex networks have been studied intensively for a decade, but research still focuses on the limited case of a single, non-interacting network1,2,3,4,5,6,7,8,9,10,11,12,13,14. Modern systems are coupled together15,16,17,18,19 and therefore should be modelled as interdependent networks. A fundamental property of interdependent networks is that failure of nodes in one network may lead to failure of dependent nodes in other networks. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of several interdependent networks. A dramatic real-world example of a cascade of failures (‘concurrent malfunction’) is the electrical blackout that affected much of Italy on 28 September 2003: the shutdown of power stations directly led to the failure of nodes in the Internet communication network, which in turn caused further breakdown of power stations20. Here we develop a framework for understanding the robustness of interacting networks subject to such cascading failures. We present exact analytical solutions for the critical fraction of nodes that, on removal, will lead to a failure cascade and to a complete fragmentation of two interdependent networks. Surprisingly, a broader degree distribution increases the vulnerability of interdependent networks to random failure, which is opposite to how a single network behaves. Our findings highlight the need to consider interdependent network properties in designing robust networks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Figure 1: Modelling a blackout in Italy.
Figure 2: Modelling an iterative process of a cascade of failures.
Figure 3: Numerical validation of theoretical results.

Similar content being viewed by others

References

  1. Watts, D. J. & Strogatz, S. H. Collective dynamics of ‘small-world’ networks. Nature 393, 440–442 (1998)

    Article  ADS  CAS  Google Scholar 

  2. Barabási, A.-L. & Albert, R. Emergence of scaling in random networks. Science 286, 509–512 (1999)

    Article  ADS  MathSciNet  Google Scholar 

  3. Albert, R. & Barabási, A.-L. Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)

    Article  ADS  MathSciNet  Google Scholar 

  4. Pastor-Satorras, R. & Vespignani, A. Evolution and Structure of the Internet: A Statistical Physics Approach (Cambridge Univ. Press, 2006)

    Google Scholar 

  5. Dorogovtsev, S. N. & Mendes, J. F. F. Evolution of Networks: From Biological Nets to the Internet and WWW. (Oxford Univ. Press, 2003)

    Book  Google Scholar 

  6. Barrat, A., Barthelemy, M. & Vespignani, A. Dynamical Processes on Complex Networks (Cambridge Univ. Press, 2009)

    MATH  Google Scholar 

  7. Cohen, R., Erez, K., ben-Avraham, D. & Havlin, S. Resilience of the Internet to random breakdown. Phys. Rev. Lett. 85, 4626–4628 (2000)

    Article  ADS  CAS  Google Scholar 

  8. Newman, M. E. J., Barabsi, A.-L. & Watts, D. J. eds. The Structure and Dynamics of Networks (Princeton Univ. Press, 2006)

    Google Scholar 

  9. Newman, M. E. J. The structure and function of complex networks. Phys. Rev. E 64, 026118 (2001)

    Article  ADS  CAS  Google Scholar 

  10. Goh, K. I., Kahng, B. & Kim, D. Universal behavior of load distribution in scale-free networks. Phys. Rev. Lett. 87, 278701 (2001)

    Article  CAS  Google Scholar 

  11. Callaway, D. S., Newman, M. E. J., Strogatz, S. H. & Watts, D. J. Network robustness and fragility: percolation on random graphs. Phys. Rev. Lett. 85, 5468–5471 (2000)

    Article  ADS  CAS  Google Scholar 

  12. Song, C. et al. Self-similarity of complex networks. Nature 433, 392–395 (2005)

    Article  ADS  CAS  Google Scholar 

  13. Motter, A. E. & Lai, Y. C. Cascade-based attacks on complex networks. Phys. Rev. E 66, 065102(R) (2002)

    Article  ADS  Google Scholar 

  14. Boccaletti, S. et al. Complex networks: structure and dynamics. Phys. Rep. 424, 175–308 (2004)

    Article  ADS  MathSciNet  Google Scholar 

  15. Peerenboom, J., Fischer, R. & Whitfield, R. Recovering from disruptions of interdependent critical infrastructures, in Proc . CRIS/DRM/IIIT/NSF Workshop Mitigat. Vulnerab. Crit. Infrastruct. Catastr. Failures (2001)

  16. Rinaldi, S., Peerenboom, J. & Kelly, T. Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Contr. Syst. Mag. 21, 11–25 (2001)

    Article  Google Scholar 

  17. Laprie, J. C., Kanoun, K. & Kaniche, M. Modeling interdependencies between the electricity and information infrastructures. SAFECOMP-2007 4680, 54–67 (2007)

    Google Scholar 

  18. Kurant, M. & Thiran, P. Layered complex networks. Phys. Rev. Lett. 96, 138701 (2006)

    Article  ADS  Google Scholar 

  19. Panzieri, S. & Setola, R. Failures propagation in critical interdependent infrastructures. Int. J. Model. Ident. Contr. 3, 69–78 (2008)

    Article  Google Scholar 

  20. Rosato, V. et al. Modelling interdependent infrastructures using interacting dynamical models. Int. J. Crit. Infrastruct. 4, 63–79 (2008)

    Article  Google Scholar 

  21. Erdős, P. & Rényi, A. On random graphs I. Publ. Math. 6, 290–297 (1959)

    MathSciNet  MATH  Google Scholar 

  22. Erdős, P. & Rényi, A. The evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci. 5, 17–61 (1960)

    MathSciNet  MATH  Google Scholar 

  23. Bollobás, B. Random Graphs (Academic, 1985)

    MATH  Google Scholar 

  24. Newman, M. E. J. Spread of epidemic disease on networks. Phys. Rev. E 66, 016128 (2002)

    Article  ADS  MathSciNet  CAS  Google Scholar 

  25. Shao, J. et al. Fractal boundaries of complex networks. Europhys. Lett. 84, 48004 (2008)

    Article  ADS  Google Scholar 

  26. Shao, J., Buldyrev, S. V., Braunstein, L. A., Havlin, S. & Stanley, H. E. Structure of shells in complex networks. Phys. Rev. E 80, 036105 (2009)

    Article  ADS  Google Scholar 

Download references

Acknowledgements

We thank R. Burk for discussions that led the authors to focus on the interesting new scientific principles governing the catastrophic collapse of coupled networks. We also thank V. Rosato for providing the Italy 2003 blackout data. S.V.B. thanks the Office of Academic Affairs of Yeshiva University for funding the Yeshiva University high-performance computer cluster and acknowledges the partial support of this research through the Dr. Bernard W. Gamson Computational Science Center at Yeshiva College. S.V.B., G.P. and H.E.S. thank the Office of Naval Research for support. S.H. thanks the European EPIWORK project and the Israel Science Foundation for financial support. We thank E. Leicht and R. de Souza for discussing their unpublished work with us.

Author Contributions S.V.B., R.P., G.P., H.E.S. and S.H. all participated equally in the conceptual design of the model, the theoretical analysis, the computer simulations and the writing of the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sergey V. Buldyrev.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Data, Supplementary References and Supplementary Figures 1- 4 with legends. (PDF 272 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Buldyrev, S., Parshani, R., Paul, G. et al. Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010). https://doi.org/10.1038/nature08932

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature08932

  • Springer Nature Limited

This article is cited by

Navigation