计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (5): 129-131.DOI: 10.3778/j.issn.1002-8331.2009.05.037

• 网络、通信、安全 • 上一篇    下一篇

链路层分类包的网络流量自相似性研究

聂得欣1,袁小坊1,2,王 东1,谢高岗2   

  1. 1.湖南大学 计算机与通信学院,长沙 410082
    2.中国科学院 计算技术研究所 下一代互联网研究中心,北京 100080
  • 收稿日期:2008-01-04 修回日期:2008-04-01 出版日期:2009-02-11 发布日期:2009-02-11
  • 通讯作者: 聂得欣

Study of self-similarity characteristic of network traffic based on classified packets of data link layer

NIE De-xin1,YUAN Xiao-fang1,2,WANG Dong1,XIE Gao-gang2   

  1. 1.College of Computer and Communication,Hunan University,Changsha 410082,China
    2.Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100080,China
  • Received:2008-01-04 Revised:2008-04-01 Online:2009-02-11 Published:2009-02-11
  • Contact: NIE De-xin

摘要: 提出一种从链路层分类包流量的角度研究网络流量自相似性的方法。使用优化的R/S(rescaled range)法计算Hurst指数,发现分类包流量和总流量一样呈自相似性,并用ON/OFF网络流量模型解释分类包流量自相似的物理原因;并使用主成分分析法研究分类包流量对总流量自相似性的影响,得出大于512 B的分类包(大象包)是影响总流量自相似性的主要原因。实验表明该方法是快速有效的。

关键词: 网络流量, 自相似性, Hurst指数, R/S法, 主成分分析法

Abstract: A novel method of studying self-similarity of network traffic is presented.By measuring online the network traffic of classified packets of a backbone link layer in OC-48 POS in a metro area network in long-term,the Hurst exponents of classified packets are been estimated by the method of R/S(rescaled range).The network traffic of the classified packets is self-similarity and the reason is explained by the ON/OFF traffic model.Then the influence of the traffic of classified packets on the self-similarity of the total traffic is researched by the method of PCA(Primary Component Analysis) and find that the self-similarity characteristic of the total traffic is mainly caused by the classified packets whose lengths are under 512 byte.Finally,the result of the experiment shows that the method is effective.

Key words: network traffic, self-similarity, Hurst exponent, R/S, Primary Component Analysis(PCA)