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by Will E. Leland, Murad S. Taqqu, Walter Willinger, Daniel V. Wilson
IEEE/ACM Transactions on Networking
http://students.cs.byu.edu/~clement/cs560/self-similar.ps.gz
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Abstract:
We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal behavior, and that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks. Intuitively, the critical characteristic of this self-similar traffic is that there is no natural length of a "burst": at every time scale ranging from a few milliseconds to minutes and hours, similar-looking traffic bursts are evident; we find that aggregating streams of such traffic typically intensifies the self-similarity ("burstiness") instead of smoothing it. Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a discussion of the underlying mathematical and statistical properties of self-similarity and their relationship with actual network behavior. We also consider some implications for congestion control in high-bandwidth networks and present traffic models based on self-similar stochastic processes that are simple, accurate, and realistic for aggregate traffic.
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