Analysis of Elephant Users in Broadband Network Traffic

  • Péter Megyesi
  • Sándor Molnár
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8115)


Elephant and mice phenomena of network traffic flows have been an interesting research area in the past decade. Several operational broadband measurement results showed that the majority of the traffic is caused by a small percentage of large flows, called the elephants. In this paper, we investigate the same phenomenon in regards of users. Our results show that even though the packet level statistics of elephant users and elephant flows show similar characteristics, there is only a small overlap between the two phenomena.


traffic measurement traffic analysis elephant flows elephant users 


  1. 1.
    Thompson, K., Miller, G., Wilder, R.: Wide Area Internet Traffic Patterns and Characteristics. IEEE Network Magazine 11(6), 10–23 (1997)CrossRefGoogle Scholar
  2. 2.
    Papagiannaki, K., Taft, N., Bhattacharyya, S., Thiran, P., Salamatian, K., Diot, C.: A pragmatic definition of elephants in internet backbone traffic. In: Proceedings of the 2nd ACM SIGCOMM Workshop on Internet Measurement (IMW 2002), Marseille, France, pp. 175–176 (2002)Google Scholar
  3. 3.
    Estan, C., Varghese, G.: New directions in traffic measurement and accounting: Focusing on the elephants, ignoring the mice. ACM Transactions on Computer Systems 21(3), 270–313 (2003)CrossRefGoogle Scholar
  4. 4.
    Brownlee, N., Claffy, K.: Understanding Internet traffic streams: dragonflies and tortoises. IEEE Communications Magazine 40(10), 110–117 (2002)CrossRefGoogle Scholar
  5. 5.
    Lan, K., Heidemann, J.: A measurement study of correlations of Internet flow characteristics. Computer Networks 50(1), 46–62 (2006)CrossRefGoogle Scholar
  6. 6.
    Markovich, N., Kilpi, J.: Bivariate statistical analysis of TCP-flow sizes and durations. Annals of Operations Research 170(1), 199–216 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Molnár, S., Móczar, Z.: Three-Dimensional Characterization of Internet Flows. In: Proceedings of IEEE International Conference on Communications (ICC 2011), Kyoto, Japan (2011)Google Scholar
  8. 8.
    Callado, A., Kamienski, C., Szabo, G., Gero, B., Kelner, J., Fernandes, S., Sadok, D.: A Survey on Internet Traffic Identification. IEEE Communications Surveys & Tutorials 11(3), 37–52 (2009)CrossRefGoogle Scholar
  9. 9.
    Sarvotham, S., Riedi, R., Baraniuk, R.: Connection-level analysis and modeling of network traffic. In: Proceedings of the 1st ACM SIGCOMM Internet Measurement Workshop (IMW 2001), San Francisco Bay Area, CA, USA, pp. 99–103 (2001)Google Scholar
  10. 10.
    Liu, P., Liu, F., Lei, Z.: Model of Network Traffic Based on Network Applications and Network Users. In: International Symposium on Computer Science and Computational Technology (ISCSCT 2008), Shanghai, China, pp. 171–174 (2008)Google Scholar
  11. 11.
    Pietrzyk, M., Plissonneau, L., Urvoy-Keller, G., En-Najjary, T.: On profiling residential customers. In: Domingo-Pascual, J., Shavitt, Y., Uhlig, S. (eds.) TMA 2011. LNCS, vol. 6613, pp. 1–14. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  12. 12.
    Molnár, S., Megyesi, P., Szabó, G.: How to Validate Traffic Generators. In: Proceedings of the 1st IEEE Workshop on Traffic Identification and Classification for Advanced Network Services and Scenarios (TRICANS 2013), Budapest, Hungary (2013)Google Scholar
  13. 13.
    The Cooperative Association for Internet Data Analysis,

Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  • Péter Megyesi
    • 1
  • Sándor Molnár
    • 1
  1. 1.High Speed Networks Laboratory, Department of Telecommunications and Media InformaticsBudapest University of Technology and EconomicsBudapestHungary

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