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A sample path approach to mean busy periods for Markov-modulated queues and fluids

Published online by Cambridge University Press:  01 July 2016

Søren Asmussen*
Affiliation:
Aalborg University
Mogens Bladt*
Affiliation:
Aalborg University
*
* Postal address for both authors: Institute of Electronic Systems, Aalborg University, Fr. Bajersv. 7, DK-9220 Aalborg, Denmark.
* Postal address for both authors: Institute of Electronic Systems, Aalborg University, Fr. Bajersv. 7, DK-9220 Aalborg, Denmark.
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Abstract

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The mean busy period of a Markov-modulated queue or fluid model is computed by an extension of the time-reversal argument connecting the steady-state distribution and the maximum of a related Markov additive process.

MSC classification

Type
Letter to the Editor
Copyright
Copyright © Applied Probability Trust 1994 

References

[1] Anick, D., Mitra, D. and Sondhi, M. M. (1982) Stochastic theory of a data-handling system with multiple sources. Bell System Tech. J. 61, 18711894.Google Scholar
[2] Asmussen, S. (1991) Ladder heights and the Markov-modulated M/G/1 queue. Stoch. Proc. Appl. 37, 313326.Google Scholar
[3] Asmussen, S. (1994) Stationary distributions for fluid flow models with or without Brownian noise. Stoch. Models 11. To appear.CrossRefGoogle Scholar
[4] Asmussen, S. (1994) Busy period analysis, rare events and transient behaviour in fluid flow models. J. Appl. Math. Stoch. Anal. To appear.Google Scholar
[5] Asmussen, S. and Bladt, M. (1994) Poisson's equation for queues driven by a Markovian marked point process. Queueing Systems 17. To appear.Google Scholar
[6] Asmussen, S. and Perry, D. (1992) On cycle maxima, first passage problems and extreme value theory for queues. Stoch. Models 8, 421458.Google Scholar
[7] Barlow, M. T., Rogers, L. C. G. and Williams, D. (1980) Wiener-Hopf factorization for matrices. Seminaire de Probabilites XIV. Lecture Notes in Mathematics 784, 324331, Springer-Verlag, Berlin.Google Scholar
[8] Gaver, D. P. and Lehoczky, J. P. (1982) Channels that cooperatively service a data stream and voice messages. IEEE Trans. Com. 30, 11531161.CrossRefGoogle Scholar
[9] Lindley, D. V. (1952) On the theory of queues with a single server. Proc. Camb. Phil. Soc. 48, 277289.Google Scholar
[10] London, R. R., Mckean, H. P., Rogers, L. C. G. and Williams, D. (1982) A martingale approach to some Wiener-Hopf problems II. Séminaire de Probabilités XVI, 6890.CrossRefGoogle Scholar
[11] Loynes, R. ?. (1962) The stability of a queue with non-independent inter-arrival and service times. Proc. Camb. Phil. Soc. 58, 497520.CrossRefGoogle Scholar
[12] Machihara, F. (1990) A new approach to the fundamental period of a queue with phase-type Markov renewal arrivals. Stoch. Models 6, 551560.Google Scholar
[13] Neuts, M. F. (1977) A versatile Markovian point process. J. Appl. Prob. 16, 764779.Google Scholar
[14] Neuts, M. F. (1981) Matrix-Geometric Solutions in Stochastic Models. Johns Hopkins University Press, Baltimore.Google Scholar
[15] Rogers, L. C. G. (1994) Fluid models in queueing theory and Wiener-Hopf factorisation of Markov chains. Ann. Appl. Prob. 4, 390413.Google Scholar