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Convergence rates in monotone separable stochastic networks

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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 languageEnglish
Pages (from-to)125-137
Number of pages13
JournalQueueing Systems
Volume52
Issue number2
DOIs
Publication statusPublished - 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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