Intra-media synchronization for multimedia communications

Maria C. Yuang*, Po-Lung Tien

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

Multimedia communications require intra-media synchronization for video data to prevent potential playout discontinuity resulting from network delay variation (jitter) while still achieving satisfactory playout throughput. In this paper, we propose a neural-network-based intra-media synchronization mechanism, called Neural Network Smoother (NNS). NNS is composed of a Neural Network (NN) Traffic Predictor, an NN Window Determinator, and a window-based playout smoothing algorithm. The NN Traffic Predictor employs an on-line-trained Back Propagation Neural Network (BPNN) to periodically predict future traffic characteristics. The NN Window Determinator determines the corresponding optimal window by means of an off-line-trained BPNN in an effort to achieve a maximum of the playout Quality (Q) value. According to the window, the window-based playout smoothing algorithm then dynamically adopts various playout rates. Compared to two other playout approaches, simulation results show that NNS achieves high-throughput and low-discontinuity playout under a variety of traffic arrivals.

Original languageEnglish
Pages480-484
Number of pages5
DOIs
StatePublished - 1 Dec 1996
EventIEEE International Conference on Industrial Technology (ICIT 96) - Shanghai, China
Duration: 2 Dec 19966 Dec 1996

Conference

ConferenceIEEE International Conference on Industrial Technology (ICIT 96)
Country/TerritoryChina
CityShanghai
Period2/12/966/12/96

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