Dynamic control of Brownian networks: State space collapse and equivalent workload formulations

J. Michael Harrison*, Jan A. Van Mieghem

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

73 Scopus citations

Abstract

Brownian networks are a class of linear stochastic control systems that arise as heavy traffic approximations in queueing theory. Such Brownian system models have been used to approximate problems of dynamic routing, dynamic sequencing and dynamic input control for queueing networks. A number of specific examples have been analyzed in recent years, and in each case the Brownian network has been successfully reduced to an "equivalent workload formulation" of lower dimension. In this article we explain that reduction in general terms, using an orthogonal decomposition that distinguishes between reversible and irreversible controls.

Original languageEnglish (US)
Pages (from-to)747-771
Number of pages25
JournalAnnals of Applied Probability
Volume7
Issue number3
DOIs
StatePublished - Aug 1997

Keywords

  • Brownian networks
  • Dynamic scheduling
  • Queueing networks
  • State space collapse

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Fingerprint Dive into the research topics of 'Dynamic control of Brownian networks: State space collapse and equivalent workload formulations'. Together they form a unique fingerprint.

Cite this