Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10498
DC FieldValueLanguage
dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorPoon, WC-
dc.creatorLo, KT-
dc.date.accessioned2015-06-23T09:11:59Z-
dc.date.available2015-06-23T09:11:59Z-
dc.identifier.issn0140-3664-
dc.identifier.urihttp://hdl.handle.net/10397/10498-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectEM algorithmen_US
dc.subjectNormal mixture distributionen_US
dc.subjectTraffic modelen_US
dc.subjectVBR videoen_US
dc.subjectVideo modelen_US
dc.titleA refined version of M/G/∞ processes for modelling VBR video trafficen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1105-
dc.identifier.epage1114-
dc.identifier.volume24-
dc.identifier.issue11-
dc.identifier.doi10.1016/S0140-3664(00)00325-X-
dcterms.abstractThis paper presents a refined version of the M/G/∞ busy-server process described in IEEE J. Select. Areas Commun., 16(5) (1998) 733-748 for VBR video modelling, with emphasis on a refined fitting approach of marginal distribution. First we suggest using normal mixture distribution instead of Gamma-Pareto distribution to model the marginal distribution for greater flexibility and accuracy. Second, we retune the parameter value of the Poisson input process to ensure smooth distribution transformation. Experimental results indicate that our model gives closer estimate to the empirical cell loss behaviour than the original model. Also, its performance is more consistent than other uni-distribution models like Gamma and lognormal, when fitting a wide variety of video sequences.-
dcterms.bibliographicCitationComputer communications, 2001, v. 24, no. 11, p. 1105-1114-
dcterms.isPartOfComputer communications-
dcterms.issued2001-
dc.identifier.scopus2-s2.0-0035875946-
dc.identifier.eissn1873-703X-
dc.identifier.rosgroupidr02139-
dc.description.ros2000-2001 > Academic research: refereed > Publication in refereed journal-
Appears in Collections:Journal/Magazine Article
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

SCOPUSTM   
Citations

17
Last Week
0
Last month
0
Citations as of Jul 27, 2020

WEB OF SCIENCETM
Citations

16
Last Week
0
Last month
0
Citations as of Aug 4, 2020

Page view(s)

138
Last Week
6
Last month
Citations as of Aug 3, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.