Assessing the Vulnerability of Network Topologies under Large-Scale Regional Failures

  • Peng, Wei (School of Computer, National University of Defense Technology) ;
  • Li, Zimu (Network Research Center, Tsinghua University) ;
  • Liu, Yujing (School of Computer, National University of Defense Technology) ;
  • Su, Jinshu (School of Computer, National University of Defense Technology)
  • Received : 2011.06.26
  • Published : 2012.08.31

Abstract

Natural disasters often lead to regional failures that can cause network nodes and links co-located in a large geographical area to fail. Novel approaches are required to assess the network vulnerability under such regional failures. In this paper, we investigate the vulnerability of networks by considering the geometric properties of regional failures and network nodes. To evaluate the criticality of node locations and determine the critical areas in a network, we propose the concept of ${\alpha}$-critical-distance with a given failure impact ratio ${\alpha}$, and we formulate two optimization problems based on the concept. By analyzing the geometric properties of the problems, we show that although finding critical nodes or links in a pure graph is a NP-complete problem, the problem of finding critical areas has polynomial time complexity. We propose two algorithms to deal with these problems and analyze their time complexities. Using real city-level Internet topology data, we conducted experiments to compute the ${\alpha}$-critical-distances for different networks. The computational results demonstrate the differences in vulnerability of different networks. The results also indicate that the critical area of a network can be estimated by limiting failure centers on the locations of network nodes. Additionally, we find that with the same impact ratio ${\alpha}$, the topologies examined have larger ${\alpha}$-critical-distances when the network performance is measured using the giant component size instead of the other two metrics. Similar results are obtained when the network performance is measured using the average two terminal reliability and the network efficiency, although computation of the former entails less time complexity than that of the latter.

Keywords

References

  1. R. Albert, H. Jeong, and A. L. Barabasi, "Error and attack tolerance of complex networks," Nature, vol. 406, pp. 378-382, 2000. https://doi.org/10.1038/35019019
  2. J. C. Doyle, D. Alderson, L. Li, S. Lowet, M. Roughan, S. Shalunov, R. Tanaka, and W. Willinger, "The 'Robust Yet Fragile' nature of the Internet," PNAS, vol. 102, no. 41, pp. 14497-14502, Oct. 2005. https://doi.org/10.1073/pnas.0501426102
  3. V. Latora and M. Marchiori, "Efficient behavior of small-world networks," Physical Review Letters, vol. 87, no. 19, 198701, Nov. 2001.
  4. A. Nagurney and Q. Qiang, "A network efficiency measure with application to critical infrastructure networks," J. Global Optimization, vol. 40, no. 1-3, pp. 261-275, Mar. 2008. https://doi.org/10.1007/s10898-007-9198-1
  5. J. Wu, M. Barahona, Y.-J. Tan, and H.-Z. Deng, "Natural connectivity of complex networks," Chinese Phys. Lett., vol. 27, no. 7, pp. 295-298, 2010.
  6. A. Jamakovic and S. Uhlig, "Influence of the network structure on robustness," in Proc. ICON, Adelaide, Australia, Nov. 2007, pp. 278-283.
  7. T. N. Dinh, Y. Xuan, M. T. Thai, and P. M. Pardalos, "On new approaches of assessing network vulnerability: Hardness and approximation," IEEE/ACM Trans. Netw., vol. 20, no. 2, pp. 609-619, 2012.
  8. A. Arulselvan, C. W. Commander, L. Elefteriadou, and P. M. Pardalos, "Detecting critical nodes in sparse graphs," Comput. Oper. Research, vol. 36, no. 7, pp. 2193-2200, July 2009. https://doi.org/10.1016/j.cor.2008.08.016
  9. Y. Xuan, Y. Shen, and My T. Thai, "A graph-theoretic QoS-aware vulnerability assessment for network topologies," in Proc. IEEE GLOBECOM, Miami, Florida, Dec. 2010, pp. 1-5.
  10. S. P. Borgatti and M. G. Everett, "A graph-theoretic perspective on centrality," Social Netw., vol. 28, no. 4, pp. 466-484, Oct. 2006. https://doi.org/10.1016/j.socnet.2005.11.005
  11. K. Wehmuth and A. Ziviani. (2011, Jan). Distributed algorithm to locate critical nodes to network robustness based on spectral analysis. Cornell University. Ithaca, NY. [Online]. Available:http://arxiv.org/abs/1101.5019 abs/1101.5019
  12. A.-M. Kermarrec, E. L. Merrer, B. Sericola, and G. Tredan, "Second order centrality: Distributed assessment of nodes criticity in complex networks," Comput. Commun., vol. 34, no. 5, pp. 619-628, Apr. 2011. https://doi.org/10.1016/j.comcom.2010.06.007
  13. T. H. Grubesic and A. T. Murray, "Vital nodes, interconnected infrastructures, and the geographies of network survivability," Annals of the Association of American Geographers, vol. 96, no. 1, pp. 64-83, 2006. https://doi.org/10.1111/j.1467-8306.2006.00499.x
  14. S. Neumayer, G. Zussman, R. Cohen, and E. Modiano, "Assessing the impact of geographically correlated network failures," in Proc. IEEE MILCOM, San Diego, California, Nov. 2008, pp. 1-6.
  15. S. Neumayer and E. Modiano, "Network reliability with geographically correlated failures," in Proc. IEEE INFOCOM, San Diego, California, Mar. 2010, pp. 1-9.
  16. B. Bassiri and S. S. Heydari, "Network survivability in large-scale regional failure scenarios," in Proc. C3S2E, Montreal, Canada, May 2009, pp. 83- 87.
  17. M. Omer, R. Nilchiani, and A. Mostashari, "Measuring the resilience of the global Internet infrastructure system," IEEE Syst. J., Sept. 2009.
  18. P. K. Agarwal, A. Efrat, S. K. Ganjugunte, D. Hay, S. Sankararaman, and G. Zussman, "Network vulnerability to single, multiple, and probabilistic physical attacks," in Proc. IEEE MILCOM, San Jose, California, Oct. 2010, pp. 1947-1952.
  19. P. K. Agarwal, A. Efrat, S. Ganjugunte, D. Hay, S. Sankararaman, and G. Zussman, "The resilience ofWDM networks to probabilistic geographical failures," in Proc. IEEE INFOCOM, Shanghai, China, Apr. 2011, pp. 891-899.
  20. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to Algorithms, 2nd. ed., MIT Press, 2001.
  21. J. Elzinga and D. W. Hearn, "The minimum covering sphere problem," Management Sci., vol. 19, pp. 96-104, 1972. https://doi.org/10.1287/mnsc.19.1.96
  22. (2011). The DIMES project. [Online]. Available: http://www.netdimes.org/
  23. (2011). MaxMind geolite city. [Online]. Available: http://www.maxmind.com/app/geolitecity/