Daniel V. Wilson

TL;DR: It is demonstrated that Ethernet LAN traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal-like behavior, and that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks.

TL;DR: In this article, the authors provide a plausible physical explanation for the occurrence of self-similarity in local-area network (LAN) traffic, based on convergence results for processes that exhibit high variability and is supported by detailed statistical analyzes of real-time traffic measurements from Ethernet LANs at the level of individual sources.

TL;DR: In this paper, the authors 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.

TL;DR: This paper provides a plausible physical explanation for the occurrence of self-similarity in high-speed network traffic based on convergence results for processes that exhibit high variability and is supported by detailed statistical analyses of real-time traffic measurements from Ethernet LAN's at the level of individual sources.

TL;DR: In this article, the authors use hundreds of millions of high-quality traffic measurements from an Ethernet local area network to demonstrate that Ethernet traffic is statistically self-similar and that this property clearly distinguishes between currently used models for packet traffic and measured data.