Please use this identifier to cite or link to this item: https://doi.org/10.1109/76.795063
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dc.titleA general AR-based technique for the generation of arbitrary gamma VBR video traffic in ATM networks
dc.contributor.authorZhang, Q.T.
dc.date.accessioned2014-10-07T02:55:42Z
dc.date.available2014-10-07T02:55:42Z
dc.date.issued1999
dc.identifier.citationZhang, Q.T. (1999). A general AR-based technique for the generation of arbitrary gamma VBR video traffic in ATM networks. IEEE Transactions on Circuits and Systems for Video Technology 9 (7) : 1130-1137. ScholarBank@NUS Repository. https://doi.org/10.1109/76.795063
dc.identifier.issn10518215
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/80273
dc.description.abstractModeling variable-bit-rate (VBR) video source traffic is a crucial issue to evaluate the end-to-end performance of transmitting video signals over asynchronous transfer mode (ATM) networks. Difficulties in source modeling arise from the fact that VBR video source traffic usually follows a gamma distribution with high correlation among adjacent data. Many researchers adopt autoregressive (AR) models driven by a Gaussian error process to account for such correlation. The problem is: due to the closure property of the Gaussian distribution, the traffic so generated is Gaussian rather than gamma. As a remedy, some researchers directly consider gamma AR models instead. Unfortunately, the trouble arises from the fact that the closure property does not apply to gamma distributions, and thus, the linear operation performed by an AR model fails to produce a gamma traffic. In this paper, we present a new technique that is capable of generating gamma-distributed traffic with arbitrary correlation while retaining the computational efficiency of Gaussian AR models. The central idea is to decompose a given gamma traffic into a linear combination of a number of χ 2(1) sequences, and each of these latter processes can be easily obtained from a Gaussian AR process through a simple nonlinear operation. Results based on actual video teleconference data are presented to verify the validity of the new algorithm. © 1999 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/76.795063
dc.sourceScopus
dc.subjectATM traffic modeling
dc.subjectGamma autoregressive models
dc.subjectGamma variable bit rate traffic
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1109/76.795063
dc.description.sourcetitleIEEE Transactions on Circuits and Systems for Video Technology
dc.description.volume9
dc.description.issue7
dc.description.page1130-1137
dc.description.codenITCTE
dc.identifier.isiut000083122000015
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