State-dependent stochastic networks. Part I. Approximations and applications with continuous diffusion limits



The Annals of Applied Probability

State-dependent stochastic networks. Part I. Approximations and applications with continuous diffusion limits

Avi Mandelbaum and Gennady Pats

Source: Ann. Appl. Probab. Volume 8, Number 2 (1998), 569-646.

Abstract

In a state-dependent queueing network, arrival and service rates, as well as routing probabilities, depend on the vector of queue lengths. For properly normalized such networks, we derive functional laws of large numbers (FLLNs) and functional central limit theorems (FCLTs). The former support fluid approximations and the latter support diffusion refinements.

The fluid limit in FLLN is the unique solution to a multidimensional autonomous ordinary differential equation with state-dependent reflection. The diffusion limit in FCLT is the unique strong solution to a stochastic differential equation with time-dependent reflection.

Examples are provided that demonstrate how such approximations facilitate the design, analysis and optimization of various manufacturing, service, communication and other systems.

Primary Subjects: 60F17, 60G17, 60J70, 60K25, 60K30
Secondary Subjects: 68M20, 90B10, 90B22, 90B30, 90C33
Keywords: Birth and death process; state-dependent networks; fluid and diffusion approximations; weak convergence; state- and time-dependent oblique reflection; congestion-dependent routing; learning systems; multiserver systems; large finite buffers; transient analysis

Full-text: Open access

Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aoap/1028903539
Mathematical Reviews number (MathSciNet): MR1624965
Digital Object Identifier: doi:10.1214/aoap/1028903539

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