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Stabilization of an Overloaded Queueing Network Using Measurement-Based Admission Control

Part of: Operations research and management science Computer system organization Special processes

Published online by Cambridge University Press:  14 July 2016

Lasse Leskelä
Lasse Leskelä*
Affiliation:
Helsinki University of Technology
*
∗ Postal address: Institute of Mathematics, PO Box 1100, FI-02015 TKK, Finland. Email address: lasse.leskela@iki.fi
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Abstract

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Admission control can be employed to avoid congestion in queueing networks subject to overload. In distributed networks, the admission decisions are often based on imperfect measurements on the network state. In this paper, we study how the lack of complete state information affects the system performance, by considering a simple network model for distributed admission control. The stability region of the network is characterized and it is shown how feedback signaling makes the system very sensitive to its parameters.

Keywords

Queueing networkadmission controlstabilityoverloadperturbed Markov process

MSC classification

Primary: 60K25: Queueing theory
Secondary: 68M20: Performance evaluation; queueing; scheduling 90B15: Network models, stochastic 90B22: Queues and service
Type
Research Papers
Information
Journal of Applied Probability , Volume 43 , Issue 1 , March 2006 , pp. 231 - 244
Copyright
© Applied Probability Trust 2006 

References

Adan, I. J. B. F., Wessels, J. and Zijm, W. H. M. (1993). Compensation approach for two-dimensional Markov processes. Adv. Appl. Prob. 25, 783–817.Google Scholar
Altman, E., Avrachenkov, K. E. and Núñez-Queija, R. (2004). Perturbation analysis for denumerable Markov chains with application to queueing models. Adv. Appl. Prob. 36, 839–853.Google Scholar
Asmussen, S. (2003). Applied Probability and Queues, 2nd edn. Springer, New York.Google Scholar
Bambos, N. and Walrand, J. (1989). On stability of state-dependent queues and acyclic queueing networks. Adv. Appl. Prob. 21, 681–701.Google Scholar
Foster, F. G. (1953). On the stochastic matrices associated with certain queuing processes. Ann. Math. Statist. 24, 355–360.Google Scholar
Leskelä, L. and Resing, J. A. C. (2004). A tandem queueing network with feedback admission control. Res. Rep. 09, 2004/2005, Institut Mittag-Leffler.Google Scholar
Meyn, S. P. and Tweedie, R. L. (1993). Stability of Markovian processes. II. Continuous-time processes and sampled chains. Adv. Appl. Prob. 25, 487–517.CrossRefGoogle Scholar
Neuts, M. F. (1981). Matrix-Geometric Solutions in Stochastic Models. Johns Hopkins University Press, Baltimore, MD.Google Scholar
Tweedie, R. L. (1975). Sufficient conditions for regularity, recurrence and ergodicity of Markov processes. Math. Proc. Camb. Philos. Soc. 78, 125–136.CrossRefGoogle Scholar