On the self-similar nature of Ethernet traffic

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.

Self-Similarity and modeling of LTE/LTE-A data traffic

“…This can be rewritten as Such self-similar time-series can be forecasted [1] and 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 [9] and helps in further optimizing the fast growing LTE network.…”

Service Differentiation in the Internet to Support Multimedia Traffic

“…Indeed, HTTP responses have been found to follow a heavy tailed distribution, corresponding to that of web files in the Internet. Moreover, the aggregate traffic generated by many users of the WWW has been shown to exhibit self-similarity [5,17].…”

System support for scalable and fault tolerant Internet services

“…In addition, the system must be able to deal with sudden bursts in load (Leland, Taqqu, Willinger & Wilson 1994, Crovella & Bestavros 1995, Gribble, Manku, Roselli, Brewer, Gibson & Miller 1998. We deal with short traffic bursts by replicating workers and directing tasks across all replicated workers for greater throughput.…”