Hostname: page-component-8448b6f56d-cfpbc Total loading time: 0 Render date: 2024-04-23T10:57:48.463Z Has data issue: false hasContentIssue false

A TIME-DEPENDENT STUDY OF THE KNOCKOUT QUEUE

Published online by Cambridge University Press:  28 March 2013

Brian Fralix*
Affiliation:
Department of Mathematical Sciences Clemson, University Clemson, SC E-mail: bfralix@clemson.edu

Abstract

We examine the time-dependent behavior of a birth–death process, whose birth rates and death rates are decreasing and increasing, respectively, with respect to the current state. Such models can be used to describe Markovian queueing systems with exponential reneging, where potential arrivals balk with a certain probability that depends on the number of customers observed upon arrival. Our results are derived by interpreting the birth–death process as the queue-length process of what we refer to as the “knockout queue.”

Type
Research Article
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Abate, J. & Whitt, W. (1987). Transient behavior of regulated Brownian motion, I: starting at the origin. Advances in Applied Probability 19, 560598.CrossRefGoogle Scholar
2.Abate, J. & Whitt, W. (1987). Transient behavior of regulated Brownian motion, II: non-zero initial conditions. Advances in Applied Probability 19, 599631.CrossRefGoogle Scholar
3.Abate, J. & Whitt, W. (1987). Transient behavior of the M/M/1 queue: starting at the origin. Queueing Systems 2, 4165.CrossRefGoogle Scholar
4.Abate, J. & Whitt, W. (1988). Transient behavior of the M/M/1 queue via Laplace transforms. Advances in Applied Probability 20, 145178.CrossRefGoogle Scholar
5.Abate, J. & Whitt, W. (1995). Calculating transient characteristics of the Erlang loss model via numerical transform inversion. Stochastic Models 14, 663680.CrossRefGoogle Scholar
6.Fralix, B.H., Riaño, G., & Serfozo, R.F. (2007). Time-dependent Palm probabilities and queueing applications. Unpublished technical report. Available from http://www.eurandom.nl/reports/2007/041-report.pdf.Google Scholar
7.Fralix, B.H. (2012). On the time-dependent moments of Markovian queues with reneging. Queueing Systems, to appear.Google Scholar
8.Fralix, B.H. & Riaño, G. (2010). A new look at transient versions of Little's law, and M/G/1 preemptive-last-come-first-served queues. Journal of Applied Probability 47, 459-473.CrossRefGoogle Scholar
9.Fralix, B.H., van Leeuwaarden, J.S.H., & Boxma, O.J. (2012). Factorization Identites for a general class of reflected processes. Available fromhttp://www.eurandom.nl/reports/2011/024-report.pdf.Google Scholar
10.Kallenberg, O. (1983). Random Measures. Berlin: Akademie-Verlag.CrossRefGoogle Scholar
11.Lindvall, T. (2002). Lectures on the Coupling Method. Mineola, New York: Dover Publications, Inc.Google Scholar
12.Mandjes, M. & Ridder, A. (2001). A large deviations approach to the transient of the Erlang loss model. Performance Evaluation 43, 181198.CrossRefGoogle Scholar
13.Neuts, M.F. (1989). Structured stochastic matrices of M/G/1-type and their applications. New York: Marcel Dekker, Inc.Google Scholar
14.Ross, S.M. (1990). Stochastic Processes, 2nd ed.New York: Wiley.Google Scholar
15.Virtamo, J. & Aalto, S. (1998). Calculation of time-dependent blocking probabilities. Proceedings of the ITC Sponsored St. Petersburg Regional International Teletraffic Seminar Teletraffic Theory as a Base for QoS: Monitoring, Evaluation, Decisions 365375. Available from:http://www.netlab.tkk.fi/tutkimus/cost257/.Google Scholar