Gaussian traffic revisited

R. de Oliveira Schmidt, R. Sadre, Aiko Pras

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    10 Citations (Scopus)
    4 Downloads (Pure)

    Abstract

    The assumption of Gaussian traffic is widely used in network modeling and planning. Due to its importance, researchers have repeatedly studied the Gaussian character of traffic aggregates. However, dedicated studies on this subject date back to 2002 and 2006. It is well known that network traffic has changed in the past few years due the the increasing use of social networks, clouds and video streaming websites. Therefore, the goal of this paper is to verify whether the Gaussianity assumption still holds for current network traffic. To this end, we study the characteristics of a large dataset, consisting of traces from four continents. The employed analysis methodology is similar to that found in previous works. In addition to the analysis of recent measurements, we also perform tests for a very long measurement period of six years. Our results show that the evolution of network traffic has not had a significant impact on its Gaussian character. Our findings also indicate that it is safer to relate the degree of Gaussianity to traffic bandwidth than to the number of users for high-speed links.
    Original languageEnglish
    Title of host publication2013 IFIP Networking Conference
    Subtitle of host publicationProceedings IFIP Networking Conference, May 22-24, 2013, Brooklyn, New York, USA
    EditorsS. Panwar
    PublisherIEEE
    Number of pages9
    ISBN (Print)978-3-901882-55-5
    Publication statusPublished - 22 May 2013
    Event12th IFIP Networking Conference 2013 - Brooklyn, United States
    Duration: 22 May 201324 May 2013
    https://networking.ifip.org/2013/index.html

    Conference

    Conference12th IFIP Networking Conference 2013
    CountryUnited States
    CityBrooklyn
    Period22/05/1324/05/13
    Internet address

    Keywords

    • EWI-23292
    • traffic models
    • IR-87972
    • Gaussianity fit
    • METIS-299964
    • Gaussian model

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  • Cite this

    de Oliveira Schmidt, R., Sadre, R., & Pras, A. (2013). Gaussian traffic revisited. In S. Panwar (Ed.), 2013 IFIP Networking Conference: Proceedings IFIP Networking Conference, May 22-24, 2013, Brooklyn, New York, USA [21] IEEE.