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Exploiting the Robustness on Power-Law Networks

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6842))

Abstract

Many complex networks are discovered to follow the power-law distribution in degree sequence, ranging from the Internet, WWW to social networks. Unfortunately, there exist a great number of threats to these complex systems. In this context, it is crucial to understand the behaviors of power-law networks under various threats. Although power-law networks have been found robust under random failures but vulnerable to intentional attacks by experimental observations, it remains hard to theoretically assess their robustness so as to design a more stable complex network. In this paper, we assess the vulnerability of power-law networks with respect to their global pairwise connectivity, i.e. the number of connected node-pairs, where a pair of nodes are connected when there is a functional path between them. According to our in-depth probabilistic analysis under the theory of random power-law graph model, our results illustrate the best range of exponential factors in which the power-law networks are almost surely unaffected by any random failures and less likely to be destructed under adversarial attacks.

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References

  1. Modeling s-t path availability to support disaster vulnerability assessment of network infrastructure. Computers & Operations Research 36(1), 16–26 (2009)

    Google Scholar 

  2. Aiello, W., Chung, F., Lu, L.: A random graph model for power law graphs. Experimental Math. 10, 53–66 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  3. Albert, R., Albert, I., Nakarado, G.L.: Structural vulnerability of the north american power grid. Phys. Rev. E 69(2), 025103 (2004)

    Article  Google Scholar 

  4. Albert, R., Jeong, H., Barabasi, A.: Error and attack tolerance of complex networks. Nature 406(6794), 378–382 (2000)

    Article  Google Scholar 

  5. Albert, R., Jeong, H., Barabasi, A.L.: The diameter of the world wide web. Nature 401, 130–131 (1999)

    Article  Google Scholar 

  6. Chung, F., Lu, L.: Connected components in random graphs with given expected degree sequences. Annals of Combinatorics, 125–145

    Google Scholar 

  7. Cohen, R., Erez, K., Ben-Avraham, D., Havlin, S.: Resilience of the Internet to Random Breakdowns. Physical Review Letters 85(21), 4626+ (2000)

    Article  Google Scholar 

  8. Dinh, T.N., Xuan, Y., Thai, M.T., Park, E.K., Znati, T.: On approximation of new optimization methods for assessing network vulnerability. In: INFOCOM, pp. 2678–2686 (2010)

    Google Scholar 

  9. Estrada, E., Hatano, N.: A vibrational approach to node centrality and vulnerability in complex networks. Physica A: Statistical Mechanics and its Applications 389(17), 3648–3660 (2010)

    Article  Google Scholar 

  10. Faloutsos, M., Faloutsos, P., Faloutsos, C.: On power-law relationships of the internet topology. In: Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, SIGCOMM 1999, pp. 251–262. ACM, New York (1999)

    Google Scholar 

  11. Holme, P., Kim, B.J., Yoon, C.N., Han, S.K.: Attack vulnerability of complex networks. Phys. Rev. E 65(5), 056109 (2002)

    Article  Google Scholar 

  12. Kaiser, M., Hilgetag, C.C.: Edge vulnerability in neural and metabolic networks. Biological Cybernetics 90, 311–317 (2004), 10.1007/s00422-004-0479-1

    Article  MATH  Google Scholar 

  13. Latora, V., Marchiori, M.: Vulnerability and protection of infrastructure networks. Phys. Rev. E 71(1), 015103 (2005)

    Article  Google Scholar 

  14. Luciano, Rodrigues, F., Travieso, G., Boas, V.P.R.: Advances in Physics

    Google Scholar 

  15. Molloy, M., Reed, B.: A critical point for random graphs with a given degree sequence. Random Struct. Algorithms 6, 161–179 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  16. Satorras, R.P., Vespignani, A.: Immunization of complex networks. Phys. Rev. E 65(3), 036104 (2002)

    Article  Google Scholar 

  17. Redner, S.: How popular is your paper? An empirical study of the citation distribution. The European Physical Journal B - Condensed Matter and Complex Systems 4(2), 131–134 (1998)

    Article  Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Shen, Y., Nguyen, N.P., Thai, M.T. (2011). Exploiting the Robustness on Power-Law Networks. In: Fu, B., Du, DZ. (eds) Computing and Combinatorics. COCOON 2011. Lecture Notes in Computer Science, vol 6842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22685-4_34

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  • DOI: https://doi.org/10.1007/978-3-642-22685-4_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22684-7

  • Online ISBN: 978-3-642-22685-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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