Service delays in strongly linked network communities

M. I. Bogachev*, N. S. Pyko, S. A. Pyko, A. N. Vasenev, A. N. Vasenev

*Corresponding author for this work

    Research output: Contribution to journalConference articleAcademicpeer-review

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    Abstract

    We analyze aggregated traffic dynamics obtained from strongly linked network communities. Our results based on two empirical data traces from university campus networks indicate that neglecting the statistical links between traffic patterns generated by individual network nodes leads to the drastic underestimation of both waiting and sojourn times. We also show that similar effects can be observed in simulated traffic patterns obtained by agent based modeling. Moreover, we suggest several indices that could be used to quantify the links between nodes and show their relation with the queuing system performance indicators.

    Original languageEnglish
    Article number012006
    JournalJournal of physics: Conference series
    Volume1352
    Issue number1
    DOIs
    Publication statusPublished - 4 Nov 2019
    EventInternational Scientific and Practical Conference on Mathematical Modeling, Programming and Applied Mathematics 2019, MMPAM 2019 - Veliky Novgorod, Russian Federation
    Duration: 27 Jun 201928 Jun 2019

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