Dynamics of Temporal Correlation in Daily Internet Traffic

Kensuke Fukuda*, Luís A.Nunes Amaral, H. Eugene Stanley

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

13 Scopus citations


In order to characterize the dynamics of self-similar behavior in daily Internet traffic, we analyze the time series of traffic volume for 24-hour period in wide-area Internet, by using detrended fluctuation analysis (DFA) - A well-known method of characterizing nonstationarity in a time series. We show that the estimated scaling exponent (which is directly related to the Hurst parameter) of traffic fluctuations has a dependency on the level of human activity for a time scale greater than 30s. Thus, the temporal correlation for traffic fluctuations is close to 1/f-noise during the day, and becomes weaker at night This result suggests that Internet traffic cannot be modeled using the unique value of the Hurst parameter.

Original languageEnglish (US)
Number of pages5
StatePublished - 2003
EventIEEE Global Telecommunications Conference GLOBECOM'03 - San Francisco, CA, United States
Duration: Dec 1 2003Dec 5 2003


OtherIEEE Global Telecommunications Conference GLOBECOM'03
Country/TerritoryUnited States
CitySan Francisco, CA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Global and Planetary Change


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