Predicting Traffic Bursts Using Extreme Value Theory

Youssouf Dahab, Abdelmahamoud and Md Said, Abas and Hasbullah, Halabi (2009) Predicting Traffic Bursts Using Extreme Value Theory. In: International Conference on Signal Acquisition and Processing 2009 (ICSAP 2009), 3-5 April 2009, Kuala Lumpur.

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Official URL: http://www.computer.org/portal/web/csdl/doi/10.110...


Traffic Bursts appear to be more pronounced recently and have major consequences for network Quality of Service. We investigate the extreme behavior of bursts and quantify the probabilities of these large bursts. Taking Bellcore internal Ethernet traces as an example, we applied Generalized Extreme Value model over block maxima. The analysis reveals that traffic burst maxima follows GEV model with negative shape parameter. Traffic bursts are in the domain of attraction of Weibull distribution. Our result confirms the conclusion of Norros of storage fed with Gaussian self-similar input.

Item Type:Conference or Workshop Item (Paper)
Subjects:T Technology > T Technology (General)
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:4585
Deposited By: Dr Halabi Hasbullah
Deposited On:18 Mar 2011 04:43
Last Modified:19 Jan 2017 08:25

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