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A unified method to analyze overtake free queueing systems

Published online by Cambridge University Press:  01 July 2016

Dimitris Bertsimas*
Affiliation:
Massachusetts Institute of Technology
Georgia Mourtzinou*
Affiliation:
Massachusetts Institute of Technology
*
Postal address: Sloan School of Management and Operations Research Center, MIT, Cambridge, MA 02139, USA.
∗∗ Postal address: Operations Research Center, MIT, Cambridge, MA 02139, USA.

Abstract

In this paper we demonstrate that the distributional laws that relate the number of customers in the system (queue), L(Q) and the time a customer spends in the system (queue), S(W) under the first-in-first-out (FIFO) discipline are special cases of the H = λG law and lead to a complete solution for the distributions of L, Q, S, W for queueing systems which satisfy distributional laws for both L and Q (overtake free systems). Moreover, in such systems the derivation of the distributions of L, Q, S, W can be done in a unified way. Consequences of the distributional laws include a generalization of PASTA to queueing systems with arbitrary renewal arrivals under heavy traffic conditions, a generalization of the Pollaczek–Khinchine formula to the G//G/1 queue, an extension of the Fuhrmann and Cooper decomposition for queues with generalized vacations under mixed generalized Erlang renewal arrivals, approximate results for the distributions of L, S in a GI/G/∞ queue, and exact results for the distributions of L, Q, S, W in priority queues with mixed generalized Erlang renewal arrivals.

Type
General Applied Probability
Copyright
Copyright © Applied Probability Trust 1996 

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Footnotes

The research of D. Bertsimas was partially supported by a Presidential Young Investigator Award DDM-9158118 with matching funds from Draper Laboratory. The research of both authors was partially supported by the National Science Foundation under grant DDM-9014751.

References

[1] Baccelli, F. and Bremaud, P. (1994) Elements of Queueing Theory: Palm-Martingale Calculus and Stochastic Recurrences. Springer, New York.Google Scholar
[2] Bertsimas, D. and Nakazato, D. (1995) The distributional Little's law and its applications. Operat. Res. 43, 298.Google Scholar
[3] Bertsimas, D. and Nakazato, D. (1992) Transient and busy period analysis of the GI/G/1 queue: The method of stages. Queueing Systems 10, 153184.CrossRefGoogle Scholar
[4] Cox, D. R. (1962) Renewal Theory. Chapman and Hall, New York.Google Scholar
[5] Doshi, B. (1985) A note on stochastic decomposition in a GI/G/1 queue with vacations or setup times. J. Appl. Prob. 22, 419428.Google Scholar
[6] Fuhrmann, S. W. and Cooper, R. B. (1985) Stochastic decompositions in a M/G/1 queue with generalized vacation. Operat. Res. 33, 11171129.Google Scholar
[7] Fuhrmann, S. W. (1985) Symmetric queues served in cyclic order. Operat. Res. Lett. 4, 139144.Google Scholar
[8] Glynn, P. W. and Whitt, W. (1991) A new view of the heavy traffic limit theorem for the infinite-server queues. Adv. Appl. Prob. 23, 188209.CrossRefGoogle Scholar
[9] Haji, R. and Newell, G. (1971) A relation between stationary queue and waiting time distributions. J. Appl. Prob. 8, 617620.Google Scholar
[10] Heyman, D. and Sobel, M. (1982) Stochastic Models in Operations Research. Vol 1. McGraw-Hill, New York.Google Scholar
[11] Jaiswal, N. K. (1968) Priority Queues. Academic Press, New York.Google Scholar
[12] Keilson, J. and Servi, L. (1988) A distributional form of Little's law. Operat. Res. Lett. 7, 223227.CrossRefGoogle Scholar
[13] Keilson, J. and Servi, L. (1990) The distributional form of Little's law and the Fuhrmann-Cooper decomposition. Operat. Res. Lett. 9, 239247.Google Scholar
[14] Kleinrock, L. (1975) Queueing Systems. Vol. 1: Theory. Wiley, New York.Google Scholar
[15] Little, J. (1961) A proof of the theorem L = ? W. Operai Res. 9, 383387.Google Scholar
[16] Lucantoni, D. M., Meier-Hellstern, K. and Neuts, M. F. (1990) A single-server queue with server vacations and a class of non-renewal arrival processes. Adv. Appl. Prob. 22, 676705.CrossRefGoogle Scholar
[17] Melamed, B. and Whitt, W. (1990) On arrivals that see time averages. Operat. Res. 38, 156172.Google Scholar
[18] Miyazawa, M. (1994) Rate conservation laws: a survey. Queueing Systems 15, 158.Google Scholar
[19] Neuts, M. F. (1975) Probability distributions of phase type. Liber Amicorum Prof. Emeritus H. Florin Department of Mathematics, University of Louvain, 173206.Google Scholar
[20] Neuts, M. F. (1986) Generalizations of the Pollaczek-Khinchine integral equation in the theory of queues. Adv. Appl. Prob. 18, 952990.Google Scholar
[21] Neuts, M. F. (1989) Structured Stochastic Matrices of M/G/1 Type and their Applications. Marcel Dekker, New York.Google Scholar
[22] Ross, S. (1985) Introduction to Probability Models. 3rd edn. Academic Press, New York.Google Scholar
[23] Smith, W. L. (1954) Asymptotic Renewal Theorems. Proc. R. Soc. Edinburgh. A 64, 948 Google Scholar
[24] Takács, L. (1962) Introduction to the Theory of Queues. Oxford University Press, New York.Google Scholar
[25] Whitt, W. (1991) A review of L = ?W and extensions. Queueing Systems. Google Scholar
[26] Wolff, R. (1989) Stochastic Modeling and the Theory of Queues. Prentice Hall, New York.Google Scholar