Dynamic resource allocation via video content and short-term traffic statistics

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)186-199
Journal / PublicationIEEE Transactions on Multimedia
Volume3
Issue number2
Publication statusPublished - Jun 2001
Externally publishedYes

Abstract

The reliable and efficient transmission of high-quality variable bit rate (VBR) video through the Internet generally requires network resources be allocated in a dynamic fashion. This includes the determination of when to renegotiate for network resources, as well as how much to request at a given time. The accuracy of any resource request method depends critically on its prediction of future traffic patterns. Such a prediction can be performed using the content and traffic information of short video segments. This paper presents a systematic approach to select the best features for prediction, indicating that while content is important in predicting the bandwidth of a video bit stream, the use of both content and available short-term bandwidth statistics can yield significant improvements. A new framework for traffic prediction is proposed in this paper; experimental results show a smaller mean-square resource prediction error and higher overall link utilization.

Research Area(s)

  • Bandwidth prediction, Dynamic resource allocation, Multimedia over IP, Neural network (NN), VBR video

Citation Format(s)

Dynamic resource allocation via video content and short-term traffic statistics. / Wu, Min; Joyce, Robert A.; Wong, Hau-San; Guan, Ling; Kung, Sun-Yuan.

In: IEEE Transactions on Multimedia, Vol. 3, No. 2, 06.2001, p. 186-199.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review