Stochastic processes for computer network traffic modeling

被引:51
作者
Lee, IWC [1 ]
Fapojuwo, AO [1 ]
机构
[1] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB T2N 1N4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
self-similarity; long-range dependence; fractals; multifractals; fractional stable motion; 1/f process; point process; infinitely divisible cascade; traffic modeling;
D O I
10.1016/j.comcom.2005.02.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 [计算机科学与技术];
摘要
Computer networks such as local area and wide area networks possess complex characteristics due to the heterogeneous nature of the supported traffic. The network traffic exhibits highly irregular fractal-like structure and long term correlations. Various stochastic processes such as fractional Gaussian noise, multiplicative cascades, linear fractional stable motion have been proposed to model network traffic. These stochastic processes are relatively unheard of in the networking community, until recently. This paper provides a thorough review of these stochastic processes and their application to wireless traffic modeling. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 23
页数:23
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