Open Access
2017 Heavy traffic approximation for the stationary distribution of a generalized Jackson network: The BAR approach
Anton Braverman, J. G. Dai, Masakiyo Miyazawa
Stoch. Syst. 7(1): 143-196 (2017). DOI: 10.1214/15-SSY199

Abstract

In the seminal paper of Gamarnik and Zeevi [17], the authors justify the steady-state diffusion approximation of a generalized Jackson network (GJN) in heavy traffic. Their approach involves the so-called limit interchange argument, which has since become a popular tool employed by many others who study diffusion approximations. In this paper we illustrate a novel approach by using it to justify the steady-state approximation of a GJN in heavy traffic. Our approach involves working directly with the basic adjoint relationship (BAR), an integral equation that characterizes the stationary distribution of a Markov process. As we will show, the BAR approach is a more natural choice than the limit interchange approach for justifying steady-state approximations, and can potentially be applied to the study of other stochastic processing networks such as multiclass queueing networks.

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Anton Braverman. J. G. Dai. Masakiyo Miyazawa. "Heavy traffic approximation for the stationary distribution of a generalized Jackson network: The BAR approach." Stoch. Syst. 7 (1) 143 - 196, 2017. https://doi.org/10.1214/15-SSY199

Information

Received: 1 August 2015; Published: 2017
First available in Project Euclid: 26 May 2017

zbMATH: 1370.60162
MathSciNet: MR3663340
Digital Object Identifier: 10.1214/15-SSY199

Keywords: heavy traffic approximation , interchange of limits , multiclass networks , Reflecting Brownian motions , single class networks , SRBM , stationary distributions , Stochastic processing networks

Vol.7 • No. 1 • 2017
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