中国邮电高校学报(英文) ›› 2011, Vol. 18 ›› Issue (5): 102-107.doi: 10.1016/S1005-8885(10)60110-0

• Networks • 上一篇    下一篇

Improved multi-fractal network traffic model and its performance analysis

黄丽亚,王锁萍   

  1. 南京邮电大学
  • 收稿日期:2011-01-28 修回日期:2011-08-01 出版日期:2011-10-31 发布日期:2011-10-13
  • 通讯作者: 黄丽亚 E-mail: huangly@njupt.edu.cn
  • 基金资助:

    This work was supported by the National Natural Science Foundation of China (61003237), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (10KJB510018).

Improved multi-fractal network traffic model and its performance analysis

  1. Institute of Electronic Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Received:2011-01-28 Revised:2011-08-01 Online:2011-10-31 Published:2011-10-13
  • Contact: Li-Ya HUANG E-mail: huangly@njupt.edu.cn
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (61003237), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (10KJB510018).

摘要:

This paper demonstrates the limitation of the traditional multi-fractal wavelet model (MWM). Through analyzing the multi-resolution behaviors of the real video traffic, we propose an improved MWM model. It synthesizes the traffic traces using another wavelet basis, and can adjust wavelet coefficients and multiplicative coefficients at each time scale, based on the network measurement. Subsequently, multifractal spectra and queue performances of the new model have been analyzed. The simulation proves it can capture the multifractal behaviors of network traces.

关键词:

multifractal, multifractal wavelet model, multifractal spectrum, queue overflow probability

Abstract:

This paper demonstrates the limitation of the traditional multi-fractal wavelet model (MWM). Through analyzing the multi-resolution behaviors of the real video traffic, we propose an improved MWM model. It synthesizes the traffic traces using another wavelet basis, and can adjust wavelet coefficients and multiplicative coefficients at each time scale, based on the network measurement. Subsequently, multifractal spectra and queue performances of the new model have been analyzed. The simulation proves it can capture the multifractal behaviors of network traces.

Key words:

multifractal, multifractal wavelet model, multifractal spectrum, queue overflow probability

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