Dynamic Control of Brownian Networks: State Space Collapse and Equivalent Workload Formulations

The Annals of Applied Probability. 7(3) 747-771, 1997

Posted: 12 Jun 2015

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Date Written: 1997

Abstract

Brownian networks are a class of linear stochastic control systems that arise as heavy traffic approximations in queuing theory. Such Brownian system models have been used to approximate problems of dynamic routing, dynamic sequencing and dynamic input control for queuing 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.

Suggested Citation

Harrison, J. Michael and Van Mieghem, Jan Albert, Dynamic Control of Brownian Networks: State Space Collapse and Equivalent Workload Formulations (1997). The Annals of Applied Probability. 7(3) 747-771, 1997, Available at SSRN: https://ssrn.com/abstract=2616973

J. Michael Harrison

Stanford Graduate School of Business ( email )

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Stanford, CA 94305-5015
United States
650-723-4727 (Phone)
650-725-6152 (Fax)

Jan Albert Van Mieghem (Contact Author)

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

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