Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80204
Title: Justifying diffusion approximations for multiclass queueing networks under a moment condition
Authors: Ye, H 
Yao, D
Keywords: Diffusion limit
Interchange of limits
Multiclass queueing network
Uniform stability
Issue Date: 2018
Publisher: Institute of Mathematical Statistics
Source: Annals of applied probability, 2018, v. 28, no. 6, p. 3652-3697 How to cite?
Journal: Annals of applied probability 
Abstract: Multiclass queueing networks (MQN) are, in general, difficult objects to study analytically. The diffusion approximation refers to using the stationary distribution of the diffusion limit as an approximation of the diffusion-scaled process (say, the workload) in the original MQN. To validate such an approximation amounts to justifying the interchange of two limits, t→∞and k→∞, with t being the time index and k, the scaling parameter. Here, we show this interchange of limits is justified under a p∗th moment condition on the primitive data, the interarrival and service times; and we provide an explicit characterization of the required order (p∗), which depends naturally on the desired order of moment of the workload process.
URI: http://hdl.handle.net/10397/80204
ISSN: 1050-5164
EISSN: 2168-8737
DOI: 10.1214/18-AAP1401
Rights: © Institute of Mathematical Statistics, 2018
The following publication Ye, H. Q., & Yao, D. D. (2018). Justifying diffusion approximations for multiclass queueing networks under a moment condition. The Annals of Applied Probability, 28(6), 3652-3697, is available at https://doi.org/10.1214/18-AAP1401
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