A novel approach to estimating hurst parameter for self-similar traffic

Di Zhang*, Min Zhang, Peida Ye

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


A variety of traffics from different communications networks have been demonstrated to show the self-similarity. A novel method to estimate the degree of self-similarity based on the index of dispersion for counts, a second-order statistic, is proposed in this paper. Its principle is introduced in brief and validation is made in detail on the basis of two self-similar process models, Sup_FRP and FBNDP. Qualification and comparison show that the method possesses simpler algorithm than the wavelet-based estimator and that it exhibits higher accuracy and reliability than the R/S estimator and the Variance-time analysis.

Original languageEnglish
Article number602216
JournalProceedings of SPIE- The International Society for Optical Engineering
Volume6022 I
Publication statusPublished - 2005
Externally publishedYes
EventNetwork Architectures, Management, and Applications III - Shanghai, China
Duration: 7 Nov 200510 Nov 2005


  • Hurst Parameter
  • Index of Dispersion for Counts
  • Self-similarity


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