On the self-similar nature of Ethernet traffic (extended version)

@article{Leland1994OnTS,
  title={On the self-similar nature of Ethernet traffic (extended version)},
  author={Will E. Leland and Murad S. Taqqu and Walter Willinger and Daniel V. Wilson},
  journal={IEEE/ACM Trans. Netw.},
  year={1994},
  volume={2},
  pages={1-15}
}
Demonstrates that Ethernet LAN traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal-like behavior, that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks, and that aggregating streams of such traffic typically intensifies the self-similarity ("burstiness") instead of smoothing it. These conclusions are supported by a rigorous statistical analysis of hundreds of millions… Expand
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A performance evaluation of the PSST model is performed by investigating its suitability to model the queueing behavior of self-similar traffic and the observed steady state queue size distribution is compared to the one predicted by aPSST model fitted to the parameters of the traffic traces. Expand
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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 suchExpand
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Two families of "fractal" arrival processes are presented which capture these features extremely compactly and the equivalence of one of these to processes with unsummable auto-correlation functions used by Leyland, Taqqu, Wilinger and Wilson (1993) to describe long term correlation and burstiness is shown. Expand
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It is shown that low order nonlinear maps can capture several of the fractal properties observed in actual data, and that the source characteristics observed inactual traffic can lead to heavy-tailed queue length distributions. Expand
On the self-similar nature of Ethernet traffic
TLDR
It is demonstrated 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 cannot be captured by existing traffic models. Expand
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The traffic on a 10-Mb/s Ethernet local-area network that connects diskless workstations to file servers in a university environment is analyzed and the distribution of packet lengths and the patterns of packet interarrival times are interpreted. Expand
Local Area Network Traffic Characteristics, with Implications for Broadband Network Congestion Management
The authors examine the phenomenon of congestion to better understand the congestion management techniques that will be needed in high-speed, cell-based networks. The first step of this study is toExpand
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