Network traffic modeling using connection-level information

Xin Wang; Shriram Sarvotham; Rudolf H. Riedi; Richard G. Baraniuk

doi:10.1117/12.475272

8 July 2002 Network traffic modeling using connection-level information

Xin Wang, Shriram Sarvotham, Rudolf H. Riedi, Richard G. Baraniuk

Proceedings Volume 4868, Scalability and Traffic Control in IP Networks II; (2002) https://doi.org/10.1117/12.475272
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States

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.

Citation Download Citation

Xin Wang, Shriram Sarvotham, Rudolf H. Riedi, and Richard G. Baraniuk "Network traffic modeling using connection-level information", Proc. SPIE 4868, Scalability and Traffic Control in IP Networks II, (8 July 2002); https://doi.org/10.1117/12.475272

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available