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

  • Heng-Chao Li
  • Wen Hong
  • Yi-Rong Wu
  • Si-Jie Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)


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.


Support Vector Machine Chaos Theory Chaotic Time Series Video Traffic Effective Prediction 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Heng-Chao Li
    • 1
    • 2
  • Wen Hong
    • 2
  • Yi-Rong Wu
    • 2
  • Si-Jie Xu
    • 3
  1. 1.Graduate School of Chinese Academy of SciencesBeijingP.R. China
  2. 2.National Key Laboratory of Microwave Imaging Technology, Institute of ElectronicsChinese Academy of SciencesBeijingP.R. China
  3. 3.Graduate School of Southwest Jiaotong UniversityChengduP.R. China

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