A Statistical Analysis of Network Parameters for the Self-management of Lambda-Connections

  • Tiago Fioreze
  • Lisandro Granville
  • Ramin Sadre
  • Aiko Pras
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5637)

Abstract

Network monitoring plays an important role in network management. Through the analysis of network parameters (e.g., flow throughput), managers can observe network behavior and make decisions based on them. The choice of network parameters although should be relevant for each specific objective. In this paper, we focus on the analysis of network parameters that are relevant for our self-management of lambda-connections proposal. This proposal consists of an automatic decision process to offload large IP flows onto lambda-connections. This paper aims at statistically analyzing a list of potential network parameters as relevant estimators for flow volume. The main contribution of this work is the introduction of a statistical methodology to validate that some few network parameters can be considered as good predictors for flow volume. These predictors are therefore of great interest to be used in our automatic decision process.

References

  1. 1.
    de Laat, C., Radius, E., Wallace, S.: The Rationale of the Current Optical Networking Initiatives. Future Gener. Comput. Syst. 19(6), 999–1008 (2003)CrossRefGoogle Scholar
  2. 2.
    Fioreze, T., van de Meent, R., Pras, A.: An Architecture for the Self-management of Lambda-Connections in Hybrid Networks. In: Pras, A., van Sinderen, M. (eds.) EUNICE 2007. LNCS, vol. 4606, pp. 141–148. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Mori, T., Uchida, M., Kawahara, R., Pan, J., Goto, S.: Identifying Elephant Flows Through Periodically Sampled Packets. In: ACM SIGCOMM, pp. 115–120 (2004)Google Scholar
  4. 4.
    Wallerich, J., Dreger, H., Feldmann, A., Krishnamurthy, B., Willinger, W.: A Methodology For Studying Persistency Aspects of Internet Flows. Computer Communication Review 35(2), 23–36 (2005)CrossRefGoogle Scholar
  5. 5.
    Thompson, K., Miller, G.J., Wilder, R.: Wide-Area Internet Traffic Patterns and Characteristics. IEEE Network 11(6), 10–23 (1997)CrossRefGoogle Scholar
  6. 6.
    Kim, M.S., Won, Y.J., Hong, J.W.: Characteristic Analysis of Internet Traffic from the Perspective of Flows. Computer Communications 29(10), 1639–1652 (2006)CrossRefGoogle Scholar
  7. 7.
    Ribeiro, B., Towsley, D., Ye, T., Bolot, J.C.: Fisher information of sampled packets: an application to flow size estimation. In: IMC 2006: Proceedings of the 6th ACM SIGCOMM conference on Internet measurement, pp. 15–26. ACM, New York (2006)Google Scholar
  8. 8.
    Raghunarayan, R.: Management Information Base for the Transmission Control Protocol (TCP). RFC 4022 (Proposed Standard) (March 2005)Google Scholar
  9. 9.
    Waldbusser, S.: Remote Network Monitoring Management Information Base Version 2. RFC 4502 (Draft Standard) (May 2006)Google Scholar
  10. 10.
    Waterman, R., Lahaye, B., Romascanu, D., Waldbusser, S.: Remote Network Monitoring MIB Extensions for Switched Networks Version 1.0. RFC 2613 (Draft Standard) (June 1999)Google Scholar
  11. 11.
    Quittek, J., Bryant, S., Claise, B., Aitken, P., Meyer, J.: Information Model for IP Flow Information Export. RFC 5102 (Proposed Standard) (January 2008)Google Scholar
  12. 12.
    Schaaf, K., Broekema, C., Diepen, G., Meijeren, E.: The Lofar Central Processing Facility Architecture. Experimental Astronomy 17(1-3), 43–58 (2004)CrossRefGoogle Scholar
  13. 13.
    Estan, C.: Internet Traffic Measurement: What’s Going on in my Network? PhD thesis (2003)Google Scholar
  14. 14.
    Brownlee, N., Claffy, K.: Understanding Internet Traffic Streams: Dragonflies and Tortoises. IEEE Communications Magazine 40(10), 110–117 (2002)CrossRefGoogle Scholar
  15. 15.
    Soule, A., Salamatia, K., Taft, N., Emilion, R., Papagiannaki, K.: Flow Classification by Histograms: or How to Go on Safari in the Internet. In: SIGMETRICS 2004/Performance 2004: Proceedings of the joint international conference on Measurement and modeling of computer systems, pp. 49–60. ACM, New York (2004)CrossRefGoogle Scholar
  16. 16.
    Lan, K., Heidemann, J.: A Measurement Study of Correlations of Internet Flow Characteristics. Computer Networks 50(1), 46–62 (2006)CrossRefGoogle Scholar
  17. 17.
    Fioreze, T., Wolbers, M.O., van de Meent, R., Pras, A.: Finding Elephant Flows for Optical Networks. In: Application session proceeding of the 10th IFIP/IEEE International Symposium on Integrated Network Management (IM 2007), Munich, Germany, Piscataway, pp. 627–640. IEEE Computer Society Press, Los Alamitos (2007)CrossRefGoogle Scholar
  18. 18.
    Fioreze, T., Wolbers, M.O., van de Meent, R., Pras, A.: Offloading IP Flows onto Lambda-Connections. In: Clemm, A., Granville, L.Z., Stadler, R. (eds.) DSOM 2007. LNCS, vol. 4785, pp. 183–186. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  19. 19.
    Fioreze, T., Wolbers, M.O., van de Meent, R., Pras, A.: Characterization of IP Flows Eligible for Lambda-Connections in Optical Networks. In: Proceedings of the 11th IEEE/IFIP Network Operations & Management Symposium (NOMS 2008), Salvador, Bahia, Brazil, Piscataway, pp. 256–262. IEEE Computer Society Press, Los Alamitos (2008)Google Scholar
  20. 20.
    Montgomery, D.C., Runger, G.C.: Applied Statistics and Probability for Engineers, 4th edn. Wiley, Chichester (2006)MATHGoogle Scholar
  21. 21.
    Pearson, K.: Mathematical Contributions to the Theory of Evolution. III. Regression, Heredity and Panmixia. Philosophical Transactions of the Royal Society A 187, 253–318 (1896)CrossRefGoogle Scholar
  22. 22.
    Kass, G.V.: An Exploratory Technique for Investigating Large Quantities of Categorical Data. Applied Statistics 29(2), 119–127 (1980)CrossRefGoogle Scholar
  23. 23.
    Moore, D.S.: The Basic Practice of Statistics, 4th edn. W. H. Freeman, New York (2006)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2009

Authors and Affiliations

  • Tiago Fioreze
    • 1
  • Lisandro Granville
    • 2
  • Ramin Sadre
    • 1
  • Aiko Pras
    • 1
  1. 1.Design and Analysis of Communication Systems (DACS)University of TwenteEnschedeThe Netherlands
  2. 2.Institute of InformaticsFederal University of Rio Grande do SulPorto AlegreBrazil

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