Dynamics of Temporal Correlation in Daily Internet Traffic

Kensuke Fukuda*, Luis A N Amaral, H. Eugene Stanley

*Corresponding author for this work

Research output: Contribution to conferencePaper

13 Scopus citations

Abstract

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)
Pages4069-4073
Number of pages5
StatePublished - Dec 1 2003
EventIEEE Global Telecommunications Conference GLOBECOM'03 - San Francisco, CA, United States
Duration: Dec 1 2003Dec 5 2003

Other

OtherIEEE Global Telecommunications Conference GLOBECOM'03
CountryUnited States
CitySan Francisco, CA
Period12/1/0312/5/03

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Global and Planetary Change

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    Fukuda, K., Amaral, L. A. N., & Stanley, H. E. (2003). Dynamics of Temporal Correlation in Daily Internet Traffic. 4069-4073. Paper presented at IEEE Global Telecommunications Conference GLOBECOM'03, San Francisco, CA, United States.