Abstract
This paper analyzes the characteristics of Internet traffic by studying a six days long trace of the entire interdomain traffic received by an ISP. Our study shows that this traffic is self-similar at time-scales spanning minutes to hours. We show that this self-similarity could be explained by two factors. First, the traffic volume received from each external source exhibits a heavy-tailed distribution. Second, the number of these external sources is also self-similar. Finally, we show that self-similar traffic can be simulated by users transferring exponentially distributed traffic provided that the number of users is self-similar.
This work was partially supported by the European Commission within the IST ATRIUM project.
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References
J. Beran. Statistics for Long-Memory Processes. Monographs on Statistics and Applied Probability, Chapman & Hall, 1994.
M. Crovella and A. Bestavros. Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes. In SIGMETRICS’96, pages 160–169, May 1996.
Cisco. NetFlow services and applications. White paper, available from http://www.cisco.com/warp/public/732/netflow, 1999.
B. Hill. A simple approach to inference about the tail of a distribution. Annals of Statistics, 3(1975), pages 1163–1174, 1975.
[LTW+94]_W. Leland, M. Taqqu, W. Willinger and D. Wilson. On the Self-Similar Nature of Ethernet Traffic (Extended Version). IEEE/A CM Transactions on Networking, February 1994.
V. Paxson and S. Floyd. Wide-Area Traffic: The Failure of Poisson Modeling. IEEE/A CM Transactions on Networking, 3(3):226–244, June 1995.
K. Park, G. Kim and M. Crovella. On the relationship between file sizes, transport protocols, and self-similar network traffic. In Proc. Fourth International Conference on Network Protocols, October 1996.
K. Park, G. Kim, and M. Crovella. On the effect of traffic self-similarity on network performance. In Proc. of SPIE International Conference on Performance and Control of Network Systems, November 1997.
S. Resnick. Heavy Tail Modeling and Teletraffic Data. Annals of Statistics, 25(1997), pages 1805–1869, 1997.
S. Resnick. Why Non-Linearities Can Ruin the Heavy-Tailed Modeler’s Day. In “A Practical Guide to Heavy Tails: Statistical Techniques and Applications”, Birkhauser, Boston, 1998.
S. Robert and J.-Y. Le Boudec. New models for self-similar traffic. Performance Evaluation 30(1-2), pages. 57–68, 1997.
S. McCreary and Claffy. Trends in wide area IP traffic patterns: a view from Ames Internet Exchange. Available from http://www.caida.org/outreach/papers/AIX0005/, 2000.
M. Taqqu, V. Teverovsky and W. Willinger. Estimators for long-range dependence: an empirical study. Fractals, (3):4:785–798, 1995.
M. Taqqu and G. Samorodnitsky. On Estimating the Intensity of Long-Range Dependence in Finite and Infinite Variance Time Series. In “A Practical Guide to Heavy Tails: Statistical Techniques and Applications”, Birkhauser, Boston, 1998.
M. Taqqu, W. Willinger, and R. Sherman. Proof of a fundamental result in self-similar traffic modeling. ACM/SIGCOMM Computer Communications Review, 27(1997), pages 5–23, 1997.
S. Uhlig and O. Bonaventure. On the Cost of Using MPLS for Interdomain Traffic. In Proc. of QOFIS2000, Berlin, September 2000.
W. Willinger, V. Paxson, and M. Taqqu. Self-similarity and heavy tails: Structural modeling of network Traffic. In “A Practical Guide to Heavy Tails: Statistical Techniques and Applications”, Birkhauser Verlag, Boston, 1998.
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Uhlig, S., Bonaventure, O. (2001). Understanding the Long-Term Self-Similarity of Internet Traffic. In: Smirnov, M.I., Crowcroft, J., Roberts, J., Boavida, F. (eds) Quality of Future Internet Services. QofIS 2001. Lecture Notes in Computer Science, vol 2156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45412-8_20
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DOI: https://doi.org/10.1007/3-540-45412-8_20
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