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Proceedings Paper

Network traffic modeling using connection-level information
Author(s): Xin Wang; Shriram Sarvotham; Rudolf H. Riedi; Richard G. Baraniuk
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Paper Abstract

Aggregate network traffic exhibits strong burstiness and non-Gaussian distributions, which popular models such as fractional Gaussian noise (fGn) fail to capture. To better understand the cause of traffic burstiness, we investigate the connection-level information of traffic traces. A careful study reveals that traffic burstiness is directly related to the heterogeneity in connection bandwidths and round-trip times and that a small number of high-bandwidth connections are solely responsible for bursts. This separation of connections has far-reaching implications on network control and leads to a new model for network traffic which we call the alpha/beta model. In this model, the network traffic is composed of two components: a bursty, non-Gaussian alpha component (stable Levy noise) and a Gaussian, long range dependent beta component (fGn). We present a fast scheme to separate the alpha and beta components of traffic using wavelet denoising.

Paper Details

Date Published: 8 July 2002
PDF: 9 pages
Proc. SPIE 4868, Scalability and Traffic Control in IP Networks II, (8 July 2002); doi: 10.1117/12.475272
Show Author Affiliations
Xin Wang, Rice Univ. (United States)
Shriram Sarvotham, Rice Univ. (United States)
Rudolf H. Riedi, Rice Univ. (United States)
Richard G. Baraniuk, Rice Univ. (United States)


Published in SPIE Proceedings Vol. 4868:
Scalability and Traffic Control in IP Networks II
Victor Firoiu; Zhi-Li Zhang, Editor(s)

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