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Research of Chaos Theory and Local Support Vector Machine in Effective Prediction of VBR MPEG Video Traffic

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Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 4113))

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Abstract

The highly bursty and time-variant characteristics of VBR MPEG video traffic make it more difficult to manage network resources, and lead to the significant reduction of network utilization. Dynamic bandwidth allocation scheme based on real-time prediction algorithms has been used to guarantee the Quality of Service (QoS). In this paper, chaos theory and local support vector machine in effective prediction of VBR MPEG video traffic is investigated. Experimental results show that our proposed scheme can effectively capture the dynamics and complexity of VBR MPEG video traffic.

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Author information

Authors and Affiliations

  1. Graduate School of Chinese Academy of Sciences, Beijing, 100080, P.R. China

    Heng-Chao Li

  2. National Key Laboratory of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing, 100080, P.R. China

    Heng-Chao Li, Wen Hong & Yi-Rong Wu

  3. Graduate School of Southwest Jiaotong University, Chengdu, 610031, P.R. China

    Si-Jie Xu

Authors
  1. Heng-Chao Li

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  2. Wen Hong

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  3. Yi-Rong Wu

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  4. Si-Jie Xu

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Editor information

Editors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China

    De-Shuang Huang

  2. Carnegie Mellon University,  

    Kang Li

  3. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Stranmillis Road, BT9 5AH, Belfast, UK

    George William Irwin

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© 2006 Springer-Verlag Berlin Heidelberg

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Li, HC., Hong, W., Wu, YR., Xu, SJ. (2006). Research of Chaos Theory and Local Support Vector Machine in Effective Prediction of VBR MPEG Video Traffic. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_154

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