Convergence rates in monotone separable stochastic networks

S. Foss; A. Sapozhnikov

doi:10.1007/s11134-006-4261-z

Convergence rates in monotone separable stochastic networks

S. Foss, A. Sapozhnikov

Research output: Contribution to journal › Article › peer-review

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Abstract

We study bounds on the rate of convergence to the stationary distribution in monotone separable networks which are represented in terms of stochastic recursive sequences. Monotonicity properties of this subclass of Markov chains allow us to formulate conditions in terms of marginal network characteristics. Two particular examples, generalized Jackson networks and multiserver queues, are considered.

Original language	English
Pages (from-to)	125-137
Number of pages	13
Journal	Queueing Systems
Volume	52
Issue number	2
DOIs	https://doi.org/10.1007/s11134-006-4261-z
Publication status	Published - Feb 2006

Keywords

Convergence rates
Coupling
Generalized Jackson network
Harris ergodic Markov chain
Moments
Monotone separable network
Multiserver queue
Renovating events

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10.1007/s11134-006-4261-z

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AB - We study bounds on the rate of convergence to the stationary distribution in monotone separable networks which are represented in terms of stochastic recursive sequences. Monotonicity properties of this subclass of Markov chains allow us to formulate conditions in terms of marginal network characteristics. Two particular examples, generalized Jackson networks and multiserver queues, are considered.

KW - Convergence rates

KW - Coupling

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KW - Harris ergodic Markov chain

KW - Moments

KW - Monotone separable network

KW - Multiserver queue

KW - Renovating events

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Convergence rates in monotone separable stochastic networks

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