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A Short-Term Forecasting Algorithm for Network Traffic Based on Chaos Theory and SVM

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Abstract

Recently, the forecasting technologies for network traffic have played a significant role in network management, congestion control and network security. Forecasting algorithms have also been investigated for decades along with the development of Time Series Analysis (TSA). Chaotic Time Series Analysis (CTSA) may be used to model and forecast the time series by Chaos Theory. As one of the prevailing intelligent forecasting algorithms, it is worthwhile to integrate CTSA and Support Vector Machine (SVM). In this paper, after the vulnerabilities of Local Support Vector Machine (LSVM) in forecasting modeling are analyzed, the Dynamic Time Wrapping (DTW) and the “Dynamic K” strategy are introduced, as well as a short-term network traffic forecasting algorithm LSVM-DTW-K based on Chaos Theory and SVM is presented. Finally, two sets of network traffic datasets collected from wired and wireless campus networks, respectively, are studied for our experiments.

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Acknowledgments

This work was partly supported by the Sichuan Provincial Basic Research Fund under grant No.2009JY0063 and the Open Research Fund of Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, as well as the Research Fund of Key Laboratory of Radio Signals Intelligent Processing, under grant No.XZD0818-09. The authors are grateful to Dr. Han Song from Curtin University of Technology, Dr. Du Xiaoping from Missouri University of Science Technology, and also grateful to all the anonymous referees.

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Authors and Affiliations

  1. School of Mathematics and Computer Engineering, Xihua University, 610039, Chengdu, China

    Xingwei Liu, Zhenhua Qin, Chun Ye & Miao Xie

  2. Key Laboratory of Information Coding and Transmission, Southwest Jiaotong University, 610031, Chengdu, China

    Xingwei Liu & Xuming Fang

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  1. Xingwei Liu
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  2. Xuming Fang
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  3. Zhenhua Qin
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  4. Chun Ye
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  5. Miao Xie
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Correspondence to Xingwei Liu.

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Liu, X., Fang, X., Qin, Z. et al. A Short-Term Forecasting Algorithm for Network Traffic Based on Chaos Theory and SVM. J Netw Syst Manage 19, 427–447 (2011). https://doi.org/10.1007/s10922-010-9188-3

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