Wireless Internet. 6th International ICST Conference, WICON 2011, Xi’an, China, October 19-21, 2011, Revised Selected Papers

Research Article

LRD Traffic Predicting Based on ARMA

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  • @INPROCEEDINGS{10.1007/978-3-642-30493-4_45,
        author={Bo Gao and Qinyu Zhang and Naitong Zhang},
        title={LRD Traffic Predicting Based on ARMA},
        proceedings={Wireless Internet. 6th International ICST Conference, WICON 2011, Xi’an, China, October 19-21, 2011, Revised Selected Papers},
        proceedings_a={WICON},
        year={2012},
        month={10},
        keywords={LRD EMD ARMA Predicting},
        doi={10.1007/978-3-642-30493-4_45}
    }
    
  • Bo Gao
    Qinyu Zhang
    Naitong Zhang
    Year: 2012
    LRD Traffic Predicting Based on ARMA
    WICON
    Springer
    DOI: 10.1007/978-3-642-30493-4_45
Bo Gao1,*, Qinyu Zhang1,*, Naitong Zhang1,*
  • 1: Harbin Institute of Technology
*Contact email: gaobo@hitsz.edu.cn, zqy@hit.edu.cn, ntzhang@hit.edu.cn

Abstract

The prediction of long range dependence (LRD) is the critical problem in network traffic. The traditional algorithms, such as Markov model and ON/OFF model, may provide high computation cost and low precision. In this study, a novel method based on empirical mode decomposition (EMD) and ARMA model was proposed. The results show that EMD could offer the function of canceling the LRD in traffic data. After transforming LRD to SRD (short range dependence) by EMD processing, the LRD traffic data could be predicted with high accuracy and low complexity by ARMA model. Meanwhile, the results indicate the usefulness of EMD in the applications of network traffic prediction.