PREDICTIVE DYNAMIC BANDWIDTH ALLOCATION FOR EFFICIENT TRANSPORT OF REAL-TIME VBR VIDEO OVER ATM

This paper presents a novel approach to dynamic transmission bandwidth allocation for transport of real-time variable-bit-rate video in ATM networks. Video traffic statistics are measured in the frequency domain: The low-frequency signal captures the slow time variation of consecutive scene changes while the high-frequency signal exhibits the feature of strong frame autocorrelation. Our queueing study indicates that the video transmission bandwidth in a finite-buffer system is essentially characterized by the low-frequency signal. We further observe in typical JPEG/MPEG video sequences that the time scale of video scene changes is in the range of a second or longer, which localizes the low-frequency video signal in a well-defined low-frequency band. Hence, in a network design it is feasible to implement dynamic allocation of video transmission bandwidth using on-line observation and prediction of scene changes. Two prediction schemes are examined: recursive least square method and time delay neural network method. A time delay neural network with low-complexity high-order architecture, called ''pi-sigma network,'' is successfully used to predict scene changes. The overall dynamic bandwidth-allocation scheme presented in this paper is shown to be promising and practically feasible in obtaining efficient transmission of real-time video traffic.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
1995-01
Language
ENG
Keywords

ORDER NEURAL NETWORKS; CAPACITY

Citation

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, v.13, no.1, pp.12 - 23

ISSN
0733-8716
URI
http://hdl.handle.net/10203/428
Appears in Collection
EE-Journal Papers(저널논문)
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