Heavy-traffic analysis for the GI/G/1 queue with heavy-tailed distributions

  • Authors:
  • O. J. Boxma;J. W. Cohen

  • Affiliations:
  • Department of Mathematics and Computing Science, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands E-mail: boxma@win.tue.nl;CWI, P.O. Box 94079, 1090 GB Amsterdam, The Netherlands

  • Venue:
  • Queueing Systems: Theory and Applications
  • Year:
  • 1999

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Abstract

We consider a GI/G/1 queue in which the service time distribution and/or the interarrival time distribution has a heavy tail, i.e., a tail behaviour like t^{-\nu} with 1, so that the mean is finite but the variance is infinite. We prove a heavy-traffic limit theorem for the distribution of the stationary actual waiting time \mathbf{W}. If the tail of the service time distribution is heavier than that of the interarrival time distribution, and the traffic load a \rightarrow 1, then \mathbf{W}, multiplied by an appropriate ‘coefficient of contraction’ that is a function of a, converges in distribution to the Kovalenko distribution. If the tail of the interarrival time distribution is heavier than that of the service time distribution, and the traffic load a \rightarrow 1, then \mathbf{W}, multiplied by another appropriate ‘coefficient of contraction’ that is a function of a, converges in distribution to the negative exponential distribution.