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Stochastic monotonicity properties of multiserver queues with impatient customers

Published online by Cambridge University Press:  14 July 2016

Partha P. Bhattacharya
Affiliation:
University of Maryland, College Park
Anthony Ephremides*
Affiliation:
University of Maryland, College Park
*
∗∗ Postal address: Electrical Engineering Department and Systems Research Center, University of Maryland, College Park, MD 20742, USA.

Abstract

We consider multiserver queues in which a customer is lost whenever its waiting time is larger than its (possibly random) deadline. For such systems, the number of (successful) departures and the number of customers lost over a time interval are the performance measures of interest. We show that these quantities are (stochastically) monotone functions of the arrival, service and deadline processes.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1991 

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Footnotes

Present address: IBM Thomas J. Watson Research Center, P.O. Box 704, Yorktown Heights, NY 10598, USA.

References

[1] Baccelli, F. and Trivedi, K. S. (1985) A single server queue in a hard real time environment. Operat. Res. Lett. 4, 161168.CrossRefGoogle Scholar
[2] Baccelli, F., Boyer, P. and Hebuterne, G. (1984) Single server queues with impatient customers. Adv. Appl. Prob. 16, 887905.CrossRefGoogle Scholar
[3] Bhattacharya, P. P. (1989) Real Time Scheduling Problems with Applications to Communication Networks. Ph.D. Dissertation, University of Maryland, College Park.Google Scholar
[4] Bhattacharya, P. P. and Ephremides, A. (1989) Optimal scheduling under strict deadlines. IEEE Trans. Autom. Control 34, 721728.CrossRefGoogle Scholar
[5] Jacobs, D. R. and Schach, S. (1972) Stochastic order relationships between GI/G/K systems. Ann. Math. Statist. 43, 16231633.CrossRefGoogle Scholar
[6] Kaspi, H. and Perry, D. (1983) Inventory systems of perishable commodities. Adv. Appl. Prob. 15, 674685.CrossRefGoogle Scholar
[7] Kaspi, H. and Perry, D. (1984) Inventory systems for perishable commodities with renewal input and Poisson output. Adv. Appl. Prob. 16, 402421.CrossRefGoogle Scholar
[8] Perry, D. and Levikson, B. (1989) Continuous production/inventory model with analogy to certain queueing and dam models. Adv. Appl. Prob. 21, 123141.CrossRefGoogle Scholar
[9] Sonderman, D. (1979) Comparing multi-server queues with finite waiting rooms, I, II. Adv. Appl. Prob. 11, 439455.CrossRefGoogle Scholar
[10] Stoyan, D. Comparison Methods for Queues and Other Stochastic Models. Wiley, New York.Google Scholar
[11] Whitt, W. (1981) Comparing counting processes and queues. Adv. Appl. Prob. 13, 207220.CrossRefGoogle Scholar
[12] Wolff, R. W. (1977) An upper bound for multi-channel queues. J. Appl. Prob. 14, 884888.Google Scholar