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On ergodicity and recurrence properties of a Markov chain by an application to an open jackson network

Part of: Special processes Markov processes

Published online by Cambridge University Press:  01 July 2016

Arie Hordijk  and
Flora Spieksma
Arie Hordijk
Affiliation:
University of Leiden
Flora Spieksma*
Affiliation:
University of Leiden
*
∗The research of this author was supported by the Netherlands Organisation for Scientific Research N.W.O.
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Abstract

This paper gives an overview of recurrence and ergodicity properties of a Markov chain. Two new notions for ergodicity and recurrence are introduced. They are called μ -geometric ergodicity and μ -geometric recurrence respectively. The first condition generalises geometric as well as strong ergodicity. Our key theorem shows that μ -geometric ergodicity is equivalent to weak μ -geometric recurrence. The latter condition is verified for the time-discretised two-centre open Jackson network. Hence, the corresponding two-dimensional Markov chain is μ -geometrically and geometrically ergodic, but not strongly ergodic. A consequence of μ -geometric ergodicity with μ of product-form is the convergence of the Laplace-Stieltjes transforms of the marginal distributions. Consequently all moments converge.

Keywords

GEOMETRICSTRONG AND μ-GEOMETRIC ERGODICITYFOSTERPOPOV AND DOEBLIN CONDITIONBOUNDING VECTOR OF PRODUCT FORMJACKSON NETWORK

MSC classification

Primary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces)
Secondary: 60K25: Queueing theory
Type
Research Article
Information
Advances in Applied Probability , Volume 24 , Issue 2 , June 1992 , pp. 343 - 376
Copyright
Copyright © Applied Probability Trust 1992 

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Footnotes

Postal address for both authors: Department of Mathematics and Computer Science, University of Leiden, Niels Bohrweg 1, 2333CA Leiden, The Netherlands.

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