Sunggon Kim, Ju Yong Lee, Student Member, IEEE, and Dan Keun Sung, Senior...  Home/Search
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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. (Update)
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BibTeX entry: (Update)
S. Kim, J. Y. Lee, and D. K. Sung, "A shifted gamma distribution model for long-range dependent internet traffic," IEEE Comun. Lett., vol. 7, pp. 124--126, Mar. 2003. http://citeseer.ist.psu.edu/kim02shifted.html More
@misc{ kim03shifted,
author = "S. Kim and J. Lee and D. Sung",
title = "A shifted gamma distribution model for long-range dependent internet traffic",
text = "S. Kim, J. Y. Lee, and D. K. Sung, A shifted gamma distribution model for
long-range dependent internet traffic, IEEE Comun. Lett., vol. 7, pp. 124--126,
Mar. 2003.",
year = "2003",
url = "citeseer.ist.psu.edu/kim02shifted.html" }
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