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Finding a Dense-Core in Jellyfish Graphs

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4863))

Abstract

The connectivity of the Internet crucially depends on the relationships between thousands of Autonomous Systems (ASes) that exchange routing information using the Border Gateway Protocol (BGP). These relationships can be modeled as a graph, called the AS-graph, in which the vertices model the ASes, and the edges model the peering arrangements between the ASes. Based on topological studies, it is widely believed that the Internet graph contains a central dense-core: Informally, this is a small set of high-degree, tightly interconnected ASes that participate in a large fraction of end-to-end routes. Finding this dense-core is a very important practical task when analyzing the Internet’s topology.

In this work we introduce a randomized sublinear algorithm that finds a dense-core of the AS-graph. We mathematically prove the correctness of our algorithm, bound the density of the core it returns, and analyze its running time. We also implemented our algorithm and tested it on real AS-graph data. Our results show that the core discovered by our algorithm is nearly identical to the cores found by existing algorithms - at a fraction of the running time.

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References

  1. Albert, R., Barabási, A.-L.: Topology of evolving networks: Local events and universality. Physical Review Letters 85(24), 5234–5237 (2000)

    Article  Google Scholar 

  2. Alvarez-Hamelin, I., Dall’Asta, L., Barrat, A., Vespignani, A.: Large scale networks fingerprinting and visualization using the k-core decomposition. Proc. Neural Information Processing Systems (August 2005)

    Google Scholar 

  3. Asahiro, Y., Iwama, K., Tamaki, H., Tokuyama, T.: Greedily finding a dense subgraph. Journal of Algorithms 34, 203–221 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  4. Bar, S., Gonen, M., Wool, A.: An incremental super-linear preferential Internet topology model. In: Barakat, C., Pratt, I. (eds.) PAM 2004. LNCS, vol. 3015, pp. 53–62. Springer, Heidelberg (2004)

    Google Scholar 

  5. Bar, S., Gonen, M., Wool, A.: A geographic directed preferential Internet topology model. Computer Networks 51(14), 4174–4188 (2007)

    Article  MATH  Google Scholar 

  6. Barford, P., Bestavros, A., Byers, J., Crovella, M.: On the marginal utility of network topology measurements. In: Proc. ACM SIGCOMM (2001)

    Google Scholar 

  7. Bianconi, G., Barabási, A.L.: Competition and multiscaling in evolving networks. Europhysics Letters 54(4), 436–442 (2001)

    Article  Google Scholar 

  8. Brunet, R.X., Sokolov, I.M.: Evolving networks with disadvantaged long-range connections. Physical Review E 66(026118) (2002)

    Google Scholar 

  9. Bu, T., Towsley, D.: On distinguishing between Internet power-law generators. In: Proc. IEEE INFOCOM 2002, New-York (April 2002)

    Google Scholar 

  10. Carmi, S., Havlin, S., Kirkpatrick, S., Shavitt, Y., Shir, E.: Medusa - new model of Internet topology using k-shell decomposition. Technical Report arXiv:cond-mat/0601240v1 (2006)

    Google Scholar 

  11. Carmi, S., Havlin, S., Kirkpatrick, S., Shavitt, Y., Shir, E.: A model of internet topology using k-shell decomposition. PNAS 2007. Proceedings of the National Academy of Sciences, USA 104(27), 11150–11154 (July 3, 2007)

    Google Scholar 

  12. Charikar, M.: Greedy approximation algorithms for finding dense components in graphs. In: Proc. APPROX (2000)

    Google Scholar 

  13. Chen, Q., Chang, H., Govindan, R., Jamin, S., Shenker, S., Willinger, W.: The origin of power laws in Internet topologies revisited. In: Proc. IEEE INFOCOM 2002, New-York (April 2002)

    Google Scholar 

  14. Faloutsos, C., Faloutsos, M., Faloutsos, P.: On power-law relationships of the Internet topology. In: Proc. of ACM SIGCOMM 1999, pp. 251–260 (August 1999)

    Google Scholar 

  15. Feige, U., Kortsarz, G., Peleg, D.: The dense k-subgraph problem. Algorithmica 29(3), 410–421 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  16. Feige, U., Langberg, M.: Approximation algorithms for maximization problems arising in graph partitioning. Journal of Algorithms 41, 174–211 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  17. Feige, U., Seltser, M.: On the densest k-subgraph problem. Technical report, Department of Applied Mathematics and Computer Science, The Weizmann Institute, Rehovot (1997)

    Google Scholar 

  18. Ge, Z., Figueiredo, D.R., Jaiswal, S., Gao, L.: On the hierarchical structure of the logical Internet graph. In: SPIE ITCOM (August 2001)

    Google Scholar 

  19. Goldreich, O., Goldwasser, S., Ron, D.: Property testing and its connections to learning and approximation. J. ACM 45, 653–750 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  20. Gonen, M., Ron, D., Weinsberg, U., Wool, A.: Finding a dense-core in jellyfish graphs. Technical report, School of Electrical Enjeneering, Tel-Aviv University (2007)

    Google Scholar 

  21. Govindan, R., Tangmunarunki, H.: Heuristics for Internet map discovery. In: Proc. IEEE INFOCOM 2000, Tel-Aviv, Israel, pp. 1371–1380 (March 2000)

    Google Scholar 

  22. Håstad, J.: Clique is hard to approximate within n 1 − ε. Acta Mathematica 182, 105–142 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  23. JUNG - the java universal network/graph framework (2007), http://jung.sourceforge.net/

  24. Krapivsky, P.L., Rodgers, G.J., Render, S.: Degree distributions of growing networks. Physical Review Letters 86(5401) (2001)

    Google Scholar 

  25. Lakhina, A., Byers, J.W., Crovella, M., Xie, P.: Sampling biases in IP topology measurments. In: Proc. IEEE INFOCOM 2003 (2003)

    Google Scholar 

  26. Li, X., Chen, G.: A local-world evolving network model. Physica A 328, 274–286 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  27. Mishra, N., Ron, D., Swaminathan, R.: A new conceptual clustering framework. Machine Learning 56, 115–151 (2004)

    Article  MATH  Google Scholar 

  28. Reittu, H., Norros, I.: On the power law random graph model of the Internet. Performance Evaluation 55 (January 2004)

    Google Scholar 

  29. Sagie, G., Wool, A.: A clustering approach for exploring the Internet structure. In: Proc. 23rd IEEE Convention of Electrical & Electronics Engineers in Israel (IEEEI) (2004)

    Google Scholar 

  30. Shavitt, Y., Shir, E.: DIMES: Let the Internet measure itself. In: Proc. ACM SIGCOMM, pp. 71–74 (2005)

    Google Scholar 

  31. Siganos, G., Tauro, S.L., Faloutsos, M.: Jellyfish: A conceptual model for the as Internet topology. Journal of Communications and Networks (2006)

    Google Scholar 

  32. Subramanian, L., Agarwal, S., Rexford, J., Katz, R.H.: Characterizing the Internet hierarchy from multiple vantage points. In: Proc. IEEE INFOCOM 2002, New-York (April 2002)

    Google Scholar 

  33. Tangmunarunkit, H., Govindan, R., Jamin, S., Shenker, S., Willinger, W.: Network topology generators: Degree based vs. structural. In: Proc. ACM SIGCOMM (2002)

    Google Scholar 

  34. Tauro, L., Palmer, C., Siganos, G., Faloutsos, M.: A simple conceptual model for Internet topology. In: IEEE Global Internet, San Antonio, TX (November 2001)

    Google Scholar 

  35. Willinger, W., Govindan, R., Jamin, S., Paxson, V., Shenker, S.: Scaling phenomena in the Internet: Critically examining criticality. Proceedings of the National Academy of Sciences of the United States of America 99, 2573–2580 (February 2002)

    Google Scholar 

  36. Winick, J., Jamin, S.: Inet-3.0: Internet topology generator. Technical Report UM-CSE-TR-456-02, Department of EECS, University of Michigan (2002)

    Google Scholar 

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Anthony Bonato Fan R. K. Chung

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© 2007 Springer-Verlag Berlin Heidelberg

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Gonen, M., Ron, D., Weinsberg, U., Wool, A. (2007). Finding a Dense-Core in Jellyfish Graphs. In: Bonato, A., Chung, F.R.K. (eds) Algorithms and Models for the Web-Graph. WAW 2007. Lecture Notes in Computer Science, vol 4863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77004-6_3

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  • DOI: https://doi.org/10.1007/978-3-540-77004-6_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77003-9

  • Online ISBN: 978-3-540-77004-6

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