Study on the Multifractal Spectrum of Local Area Networks Traffic and Their Correlations

Conference paper


Due to the singularity in the Local Area Network (LAN) traffic, the multifractal spectrums are used to study the characteristics of network traffic from the viewpoint of nonlinear dynamic system. First, the multifractal spectrums of the LAN traffic are introduced and established to investigate the complex features of the systems. Then, the distributions of spectrum parameter vs. the network traffic are studied in detail, and some important phenomena, which are related with the complicated networks traffic, are captured. Furthermore, the correlations between multifractal spectrum and logarithm of mean traffic are presented, and they can be feasibly applied to the prediction for the networks traffic. Some conclusions can be drawn that the variation of width of multifractal spectrum is similar to that of network traffic in a sense. To some degree, the difference between maximum and minimum probability of multifractal spectrum is ahead to the oscillation of network traffic, and it is a fundamental route for the network traffic prediction.


  1. 1.
    Levy VJ, Sikdar B (2001) A multiplicative multifractal model for TCP traffic [J]. In: IEEE symposium on computers and communications-proceedings, pp 714–719Google Scholar
  2. 2.
    Feldmann A, Gilbert AC, Willinger W (1998) Data networks as cascades: investigating the multifractal nature of internet WAN traffic [J]. Comput Commun Rev 28(4):42–55CrossRefGoogle Scholar
  3. 3.
    Lacovoni G, Mance V, Verqni D (2000) Single source TCP behaviour: a multifractal analysis, conference record [J]. In: IEEE global telecommunications conference, vol 1, pp 323–328Google Scholar
  4. 4.
    Feldmann A, Gilbert AC, Willinger W, et al (1998) The changing nature of network traffic: scaling phenomena [J]. ACM SIGCOMM Comput Commun Rev 28(2):5–29CrossRefGoogle Scholar
  5. 5.
    Jackson JK (1957) Network of waiting lines [J]. Oper Res 5:518–521CrossRefGoogle Scholar
  6. 6.
    Beran J, Sherman R, Taqqu MS, et al (1995) Long-range dependence in variable-bit-rate video traffic [J]. IEEE Trans Commun 43(2):1566–1579CrossRefGoogle Scholar
  7. 7.
    Rao Y, Xu Z, Liu Z (2004) Length requirement of self-similar network traffic [J]. Chin J Electron 13(1):175–178Google Scholar
  8. 8.
    Riedi R (1995) An improved multifractal formalism and self-similar measures [J]. J Math Anal Appl 189:462–490MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Energy and Power EngineeringXi’an Jiaotong UniversityXi’anPeople’s Republic of China

Personalised recommendations