Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/80204
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Logistics and Maritime Studies | - |
dc.creator | Ye, H | - |
dc.creator | Yao, D | - |
dc.date.accessioned | 2019-01-08T03:03:13Z | - |
dc.date.available | 2019-01-08T03:03:13Z | - |
dc.identifier.issn | 1050-5164 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/80204 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Mathematical Statistics | en_US |
dc.rights | © Institute of Mathematical Statistics, 2018 | en_US |
dc.rights | 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 | en_US |
dc.rights | Posted with permission of the publisher. | en_US |
dc.subject | Diffusion limit | en_US |
dc.subject | Interchange of limits | en_US |
dc.subject | Multiclass queueing network | en_US |
dc.subject | Uniform stability | en_US |
dc.title | Justifying diffusion approximations for multiclass queueing networks under a moment condition | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 3652 | en_US |
dc.identifier.epage | 3697 | en_US |
dc.identifier.volume | 28 | en_US |
dc.identifier.issue | 6 | en_US |
dc.identifier.doi | 10.1214/18-AAP1401 | en_US |
dcterms.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. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Annals of applied probability, 2018, v. 28, no. 6, p. 3652-3697 | - |
dcterms.isPartOf | Annals of applied probability | - |
dcterms.issued | 2018 | - |
dc.identifier.isi | WOS:000446578800010 | - |
dc.identifier.scopus | 2-s2.0-85054979786 | - |
dc.identifier.eissn | 2168-8737 | en_US |
dc.description.validate | 201901 bcma | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Ye_Justifying_diffusion_approximations.pdf | 406.21 kB | Adobe PDF | View/Open |
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