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A new look at transient versions of Little's law, and M/G/1 preemptive last-come-first-served queues

Published online by Cambridge University Press:  14 July 2016

Brian H. Fralix*
Affiliation:
EURANDOM and Eindhoven University of Technology
Germán Riaño*
Affiliation:
Universidad de los Andes, Colombia
*
Current address: Department of Mathematical Sciences, Clemson University, O-110 Martin Hall, Box 340975, Clemson, SC 29634, USA. Email address: bfralix@clemson.edu
∗∗Current address: Strategic Operations Research Team, Kimberly-Clark, Latin America Operations, Bogotá, Colombia.
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Abstract

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We take a new look at transient, or time-dependent Little laws for queueing systems. Through the use of Palm measures, we show that previous laws (see Bertsimas and Mourtzinou (1997)) can be generalized. Furthermore, within this framework, a new law can be derived as well, which gives higher-moment expressions for very general types of queueing system; in particular, the laws hold for systems that allow customers to overtake one another. What is especially novel about our approach is the use of Palm measures that are induced by nonstationary point processes, as these measures are not commonly found in the queueing literature. This new higher-moment law is then used to provide expressions for all moments of the number of customers in the system in an M/G/1 preemptive last-come-first-served queue at a time t > 0, for any initial condition and any of the more famous preemptive disciplines (i.e. preemptive-resume, and preemptive-repeat with and without resampling) that are analogous to the special cases found in Abate and Whitt (1987c), (1988). These expressions are then used to derive a nice structural form for all of the time-dependent moments of a regulated Brownian motion (see Abate and Whitt (1987a), (1987b)).

Type
Research Article
Copyright
Copyright © Applied Probability Trust 2010 

References

[1] Abate, J. and Whitt, W. (1987a). Transient behavior of regulated Brownian motion. I. Starting at the origin. Adv. Appl. Prob. 19, 560598.Google Scholar
[2] Abate, J. and Whitt, W. (1987b). Transient behavior of regulated Brownian motion. II. Nonzero initial conditions. Adv. Appl. Prob. 19, 599631.CrossRefGoogle Scholar
[3] Abate, J. and Whitt, W. (1987c). Transient behavior of the M/M/1 queue: starting at the origin. Queueing Systems 2, 4165.CrossRefGoogle Scholar
[4] Abate, J. and Whitt, W. (1988). Transient behavior of the M/M/1 queue via Laplace transforms. Adv. Appl. Prob. 20, 145178.Google Scholar
[5] Baccelli, F. and Brémaud, P. (2003). Elements of Queueing Theory, 2nd edn. Springer, Berlin.Google Scholar
[6] Bertsimas, D. and Mourtzinou, G. (1997). Transient laws of non-stationary queueing systems and their applications. Queueing Systems 25, 115155.CrossRefGoogle Scholar
[7] Bertsimas, D. and Nakazato, D. (1995). The distributional Little's law and its applications. Operat. Res. 43, 298310.CrossRefGoogle Scholar
[8] Błaszczyszyn, B. (1995). Factorial moment expansion for stochastic systems. Stoch. Process. Appl. 56, 321335.Google Scholar
[9] Błaszczyszyn, B., Rolski, T. and Schmidt, V. (1995). Light-traffic approximation in queues and related stochastic models. In Advances in Queueing, CRC Press, Boca Raton, FL, pp. 379406.Google Scholar
[10] Denisov, D. and Sapozhnikov, A. (2006). On the distribution of the number of customers in the symmetric M/G/1 queue. Queueing Systems 54, 237241.Google Scholar
[11] Fralix, B. H. (2008). A time-dependent view of the ASTA problem, with applications to preemptive queues and birth-death processes. Submitted.Google Scholar
[12] Haji, R. and Newell, G. F. (1971). A relation between stationary queue and waiting time distributions. J. Appl. Prob. 8, 617620.CrossRefGoogle Scholar
[13] Kallenberg, O. (1983). Random Measures, 3rd edn. Akademie, Berlin.Google Scholar
[14] Keilson, J. and Servi, L. D. (1988). A distributional form of Little's law. Operat. Res. Lett. 7, 223227.Google Scholar
[15] Kelly, F. P. (1979). Reversibility and Stochastic Networks. John Wiley, Chichester.Google Scholar
[16] Kella, O., Zwart, B. and Boxma, O. (2005). Some time-dependent properties of symmetric M/G/1 queues. J. Appl. Prob. 42, 223234.CrossRefGoogle Scholar
[17] Kitaev, M. Y. (1993). The M/G/1 processor-sharing model: transient behavior. Queueing Systems 14, 239273.Google Scholar
[18] Riaño, G. (2002). Transient behavior of stochastic networks: application to production planning with load-dependent lead times. , Georgia Institute of Technology.Google Scholar
[19] Rolski, T. (1989). Relationships between characteristics in periodic Poisson queues. Queueing Systems 4, 1726.CrossRefGoogle Scholar
[20] Ryll-Nardzewski, C. (1961). Remarks on processes of calls. In Proc. 4th Berkeley Symp. Math. Statist. Prob., Vol. II, University of California Press, Berkeley, pp. 455465.Google Scholar
[21] Serfozo, R. F. (1999). Introduction to Stochastic Networks. Springer, New York.Google Scholar
[22] Whitt, W. (1991). A review of L = λ W and extensions. Queueing Systems 9, 235268.Google Scholar