• DocumentCode
    1402442
  • Title

    The M/G/1 queue with heavy-tailed service time distribution

  • Author

    Boxma, Onno J. ; Cohen, J.W.

  • Author_Institution
    CWI, Amsterdam, Netherlands
  • Volume
    16
  • Issue
    5
  • fYear
    1998
  • fDate
    6/1/1998 12:00:00 AM
  • Firstpage
    749
  • Lastpage
    763
  • Abstract
    In modern teletraffic applications of queueing theory, service time distributions B(t) with a heavy tail occur, i.e., 1-B(t)~Ct-v for t→∞ with v>1. For such service time distributions, not much explicit information is available concerning the tail probabilities of the corresponding waiting time distribution W(t). In the present study, which is devoted to the M/G/1 queue, a class of heavy-tailed service time distributions is introduced that does allow a rather detailed analysis of the tail behavior of the waiting time distribution. For v=1½, an explicit expression for W(t) is derived. For rational v with 1<v<2, an asymptotic series for the tail probabilities of W(t) is derived. In addition, we present an approximation for W(t), which is based on a heavy-traffic limit theorem for the M/G/1 queue with heavy-tailed service time distribution (with infinite variance); this approximation is shown to yield excellent results for values of t which are not too small, even when the load is not heavy
  • Keywords
    approximation theory; probability; queueing theory; series (mathematics); statistical analysis; telecommunication traffic; M/G/1 queue; approximation; asymptotic series; explicit expression; heavy-tailed service time distribution; heavy-traffic limit theorem; infinite variance; queueing theory; tail probabilities; teletraffic applications; waiting time distribution; Area measurement; Ethernet networks; Local area networks; Probability distribution; Queueing analysis; Tail; Telecommunication traffic; Time measurement; Traffic control; Wide area networks;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/49.700910
  • Filename
    700910