A shifted gamma distribution model for long-range dependent Internet traffic

Sunggon Kim; Ju Yong Lee; Dan Keun Sung

doi:10.1109/LCOMM.2002.808400

A shifted gamma distribution model for long-range dependent Internet traffic

Sunggon Kim, Ju Yong Lee, Dan Keun Sung

Department of Statistics

Korea Advanced Institute of Science and Technology

Research output: Contribution to journal › Article › peer-review

47 Scopus citations

Abstract

It is important to characterize the distributional property and the correlation structure of traffic arrival processes in modeling internet traffic. The conventional fractional Gaussian noise(fGn) model fails in characterizing the distributional property when the distribution of the input traffic rates is nongaussian. We propose a shifted gamma distribution model which can solve this problem. A linear-time generation algorithm is also given.

Original language	English
Pages (from-to)	124-126
Number of pages	3
Journal	IEEE Communications Letters
Volume	7
Issue number	3
DOIs	https://doi.org/10.1109/LCOMM.2002.808400
State	Published - Mar 2003

Keywords

Fractional Gaussian noise
Internet traffic modeling
Long-range dependence
Shifted gamma distribution

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10.1109/LCOMM.2002.808400

Cite this

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abstract = "It is important to characterize the distributional property and the correlation structure of traffic arrival processes in modeling internet traffic. The conventional fractional Gaussian noise(fGn) model fails in characterizing the distributional property when the distribution of the input traffic rates is nongaussian. We propose a shifted gamma distribution model which can solve this problem. A linear-time generation algorithm is also given.",

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AB - It is important to characterize the distributional property and the correlation structure of traffic arrival processes in modeling internet traffic. The conventional fractional Gaussian noise(fGn) model fails in characterizing the distributional property when the distribution of the input traffic rates is nongaussian. We propose a shifted gamma distribution model which can solve this problem. A linear-time generation algorithm is also given.

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KW - Long-range dependence

KW - Shifted gamma distribution

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A shifted gamma distribution model for long-range dependent Internet traffic

Abstract

Keywords

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