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期刊论文
The Impact of Non-Gaussian Distribution Traffic on Network Performance
J. Comput. Sci. & Technol. Vol. 17 No.1 Jan. 2002,-0001,():
Recent extensive measurements of real-life traffic demonstrate that the probability density function of the traffic is noa-Gaussian. If a traffic model does not capture this characteristics, any analytical or simulation results will not be accurate. In this work, we study the impact of non-Gausslan traffic on network performance, and present an approach that can accurately model the marginal distribution of real-life traffic. Both the long- and short-range autocorrelations are also accounted. We show that the removal of non-Gaussian components of the process does not change its correlation structure, and we validate our promising procedure by simulations.
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