Heavy-traffic asymptotics for networks of parallel queues with Markov-modulated service speeds

J.L. Dorsman, M. Vlasiou, B. Zwart

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)


We study a network of parallel single-server queues, where the speeds of the servers are varying over time and governed by a single continuous-time Markov chain. We obtain heavy-traffic limits for the distributions of the joint workload, waiting-time and queue length processes. We do so by using a functional central limit theorem approach, which requires the interchange of steady-state and heavy-traffic limits. The marginals of these limiting distributions are shown to be exponential with rates that can be computed by matrix-analytic methods. Moreover, we show how to numerically compute the joint distributions, by viewing the limit processes as multi-dimensional semi-martingale reflected Brownian motions in the non-negative orthant. Keywords: Functional central limit theorem; Layered queueing networks; Machine-repair model; Semi-martingale reflected Brownian motion
Original languageEnglish
Pages (from-to)293-319
Number of pages27
JournalQueueing systems
Issue number3
Publication statusPublished - 2015
Externally publishedYes


Dive into the research topics of 'Heavy-traffic asymptotics for networks of parallel queues with Markov-modulated service speeds'. Together they form a unique fingerprint.

Cite this