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On the Impact of Clustering on Measurement Reduction

(Work in Progress)
  • Damien Saucez
  • Benoit Donnet
  • Olivier Bonaventure
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5550)

Abstract

Measuring a path performance according to one or several metrics, such as delay or bandwidth, is becoming more and more popular for applications. However, constantly probing the network is not suitable. To make measurements more scalable, the notion of clustering has emerged. In this paper, we demonstrate that clustering can limit the measurement overhead in such a context without loosing too much accuracy. We first explain that measurement reduction can be observed when vantage points collaborate and use clustering to estimate path performance. We then show, with real traces, how effective is the overhead reduction and what is the impact in term of measurement accuracy.

Keywords

clustering BGP reduction measurement 

References

  1. 1.
    Cheswick, B., Burch, H., Branigan, S.: Mapping and visualizing the internet. In: Proc. USENIX Annual Technical Conference (June 2000)Google Scholar
  2. 2.
    Brown, G.: Internet address space clustering for intelligent route control (2004), see: http://www.cs.indiana.edu/~geobrown/journal-new.pdf
  3. 3.
    Szymaniak, M., Presotto, D., Pierre, G., Van Steen, M.: Practical large-scale latency estimation. Computer Networks 52(7), 1343–1364 (2008)CrossRefGoogle Scholar
  4. 4.
    Krishnamurthy, B., Wang, J.: On network-aware clustering of web clients. In: Proc. ACM SIGCOMM (August 2000)Google Scholar
  5. 5.
    Ng, T., Zhang, H.: Predicting Internet network distance with coordinates-based approaches. In: Proc. IEEE INFOCOM (June 2002)Google Scholar
  6. 6.
    Ng, T.S.E., Zhang, H.: A network positioning system for the Internet. In: Proc. USENIX Annual Technical Conference (June 2004)Google Scholar
  7. 7.
    Dabek, F., Cox, R., Kaashoek, K., Morris, R.: Vivaldi, a decentralized network coordinated system. In: Proc. ACM SIGCOMM (August 2004)Google Scholar
  8. 8.
    Donnet, B., Raoult, P., Friedman, T., Crovella, M.: Efficient algorithms for large-scale topology discovery. In: Proc. ACM SIGMETRICS (June 2005)Google Scholar
  9. 9.
    Donnet, B., Friedman, T., Crovella, M.: Improved algorithms for network topology discovery. In: Dovrolis, C. (ed.) PAM 2005. LNCS, vol. 3431, pp. 149–162. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  10. 10.
    Hu, N., Steenkiste, P.: Exploiting Internet route sharing for large-scale available bandwidth estimation. In: Proc. ACM/Usenix Internet Measurement Conference, IMC (October 2005)Google Scholar
  11. 11.
    Ramasubramanian, V., Malhki, D., Kuhn, F., Abraham, I., Balakrishnan, M., Gupta, A., Akella, A.: A unified network coordinate system for bandwidth and latency. Technical Report MSR-TR-2008-124, Microsoft Research (September 2008)Google Scholar
  12. 12.
    Krishnamurthy, B., Wang, J.: Topology modeling via cluster graphs. In: Proc. ACM SIGCOMM Workshop on Internet Measurement, IMW (November 2001)Google Scholar
  13. 13.
    MaxMind: Geolocation and online fraud prevention from maxmind (2002), See: http://www.maxmind.com/
  14. 14.
    Siwpersad, S., Gueye, B., Uhlig, S.: Assessing the geographic resolution of exhaustive tabulation for geolocating Internet hosts. In: Claypool, M., Uhlig, S. (eds.) PAM 2008. LNCS, vol. 4979, pp. 11–20. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Madhyastha, H.V., Isdal, T., Piatek, M., Dixon, C., Anderson, T., Krishnamurthy, A., Venkataramani, A.: iPlane: An information plane for distributed services. In: Proc. USENIX Symposium on Operating Systems Design and Implementation, OSDI (November 2006), http://iplane.cs.washington.edu
  16. 16.
    Team Cymru: Internet security research and insight (2004), See: http://www.team-cymru.org/
  17. 17.
    Yalagandula, P., Sharma, P., Banerjee, S., Lee, S.J., Basu, S.: S3: A scalable sensing service for monitoring large networked systems. In: Proc. ACM SIGCOMM Workshop on Internet Network Measurement, INM (September 2006)Google Scholar
  18. 18.
    Leonard, D., Loguinov, D.: Turbo King: Framework for large-scale Internet delay measurements. In: Proc. IEEE INFOCOM (April 2008)Google Scholar
  19. 19.
    Mahajan, R., Zhang, M., Poole, L., Pai, V.: Uncovering performance differences among backbone ISPs with NetDiff. In: Proc. Symposium on Network Systems Design and Implementation (NSDI) (April 2008)Google Scholar
  20. 20.
    Claffy, K., Hyun, Y., Keys, K., Fomenkov, M.: Internet mapping: from art to science. In: Proc. IEEE Cybersecurity Applications and Technologies Conference for Homeland Security, CATCH (March 2009)Google Scholar
  21. 21.
    University of Oregon: Route views, University of Oregon Route Views project, http://www.routeviews.org/

Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Damien Saucez
    • 1
  • Benoit Donnet
    • 1
  • Olivier Bonaventure
    • 1
  1. 1.CSE DeparmentUniversitè catholique de LouvainBelgium

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