2nd International ICST Conference on Performance Evaluation Methodologies and Tools

Research Article

A Binomial Measure Method for Traffic Modeling

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  • @INPROCEEDINGS{10.4108/valuetools.2007.1945,
        author={Lingbo Pei and Ming Chen and Jun Zhou},
        title={A Binomial Measure Method for Traffic Modeling},
        proceedings={2nd International ICST Conference on Performance Evaluation Methodologies and Tools},
        proceedings_a={VALUETOOLS},
        year={2010},
        month={5},
        keywords={Nonstationary Poisson characteristic self-similarity multifractal binomial measure method.},
        doi={10.4108/valuetools.2007.1945}
    }
    
  • Lingbo Pei
    Ming Chen
    Jun Zhou
    Year: 2010
    A Binomial Measure Method for Traffic Modeling
    VALUETOOLS
    ICST
    DOI: 10.4108/valuetools.2007.1945
Lingbo Pei1,*, Ming Chen1,*, Jun Zhou1,*
  • 1: Institute of Command Automation PLA University of Science and Technology Nanjing China
*Contact email: gemini_nj@126.com, mingchen@public1.ptt.js.cn, Zhouj_nj@126.com

Abstract

According to some discoveries and analysis results of network measurement in modern communication networks in recent years, much literature has proven that traffic present the nonstationary Poisson characteristic at sub-second time scales in IP backbone, which not accord with self-similarity characteristic for last decade. This paper presents the binomial measure method for traffic characteristic analysis. Some novel properties about the method are also discussed. The method can produces a time series with self-similarity characteristic, and more, realizes the transition from self-similarity distribution to Poisson one. The validity of the method is verified by simulation experiments on NS2. The purpose of the paper is to provide a comprehensive presentation of the binomial measure method base multifractal theory in traffic engineering field.