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Heavy-tailed dependent queues in heavy traffic

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Języki publikacji
EN
Abstrakty
EN
The paper studies G/G/1 queues with heavy-tailed probability distributions of the service times and/or the interarrival times. It relies on the fact that the heavy traffic limiting distribution of the normalized stationary waiting times for such queues is equal to the distribution of the supremum M = sup0 ≤ t < ∞ (X(t)−βt), where X is a Lévy process. This distribution turns out to be exponential if the tail of the distribution of interarrival times is heavier than that of the service times, and it has a more complicated non-exponential shape in the opposite case; if the service times have heavy-tailed distribution in the domain of attraction of a one-sided α-stable distribution, then the limit distribution is Mittag-Leffler’s. In the case of a symmetric α-stable process X, the Laplace transform of the distribution of the supremum M is also given. Taking into account the known relationship between the heavy-traffic-regime distribution of queue length and its waiting time, asymptotic results for the former are also provided. Statistical dependence between the sequence of service times and the sequence of interarrival times, as well as between random variables within each of these two sequences, is allowed. Several examples are provided.
Rocznik
Strony
67--96
Opis fizyczny
Bibliogr. 16 poz.
Twórcy
autor
  • Institute of Mathematics, University of Wrocław, 50-384 Wrocław, Poland
  • Department of Statistics, and the Center for Stochastic and Chaotic Processes in Science and Technology, Case Western Reserve University, Cleveland, OH 44106, U.S.A.
Bibliografia
  • [1] P. Billingsley, Convergence of Probability Measures, Wiley, New York 1968.
  • [2] N. H. Bingham, Fluctuation theory in continuous time, Adv. in Appl. Probab. 7 (1975), pp. 705-766.
  • [3] O. J. Boxma and J. W. Cohen, Heavy-traffic analysis for GI/G/1 queue with heavy-tailed distributions, Queueing Systems 33 (1999), pp. 177-204.
  • [4] R. Durrett and S. I. Resnik, Functional limit theorems for dependent variables, Ann. Probab. 6 (1978), pp. 829-846.
  • [5] M. Iosifescu and R. Theodorescu, Random Processes and Learning, Springer, 1969.
  • [6] A. Jakubowski, Principle of conditioning in limit theorems for sums of random variables, Ann. Probab. 14 (1986), pp. 902-913.
  • [7] S. Karlin and H. M. Taylor, A First Course in Stochastic Processes, Academic Press INC (London), 1975.
  • [8] J. F. Kingman, The single server queue in heavy traffic, Proc. Cambridge Philos. Soc. 57 (1961), pp. 902-904.
  • [9] S. Kwapień and W. A. Woyczyński, Random Series and Stochastic Integrals: Single and Multiple, Birkhäuser, Boston 1992.
  • [10] V. V. Petrov, Sums of Independent Random Variables, Akademie-Verlag, Berlin 1975.
  • [11] Yu. V. Prokhorov, Convergence of Random Processes and Limit Theorems in Probability Theory, Theory Probab. Appl. Vol. 1 (1956), pp. 157-214.
  • [12] D. Stoyan, Comparison Methods for Queues and Other Stochastic Models, Wiley, 1983.
  • [13] W. Szczotka, Exponential approximation of waiting time and queue size for queues in heavy traffic, Adv. in Appl. Probab. 22 (1990), pp. 230-240.
  • [14] W. Szczotka, Tightness of the stationary waiting time in heavy traffic, Adv. in Appl. Probab. 31 (1999), pp. 788-794.
  • [15] W. Szczotka and W. A. Woyczyński, Distributions of suprema of Lévy processes via the Heavy Traffic Invariance Principle, Probab. Math. Statist. 23 (2003), pp. 251-272.
  • [16] W. Whitt, Stochastic-Process Limits. An introduction to Stochastic-Process Limits and Their Application to Queues, Springer, New York 2002.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-453cf626-a3b1-42b2-b468-d0b5cc381283
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