Video adaptation for stored video delivery over resource-constrained networks

This project studies content adaptation and bandwidth smoothing techniques for stored video delivery over resource-constrained networks. For the content adaptation approach, we apply the digital item adaptation standard defined in the MPEG-21 multimedia framework to maximize the bandwidth resource u...

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Main Author: Tao, DaYong
Other Authors: Cai Jianfei
Format: Theses and Dissertations
Published: 2008
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Online Access:https://hdl.handle.net/10356/2465
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-24652023-03-04T00:43:37Z Video adaptation for stored video delivery over resource-constrained networks Tao, DaYong Cai Jianfei School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks This project studies content adaptation and bandwidth smoothing techniques for stored video delivery over resource-constrained networks. For the content adaptation approach, we apply the digital item adaptation standard defined in the MPEG-21 multimedia framework to maximize the bandwidth resource utilization and deliver the best quality video given the constraint user environment. The bandwidth smoothing approach presents an optimal frame selection algorithm under limited channel bandwidth and constrained client buffer condition. In addition, a novel reverse frame selection algorithm has been proposed that can find all the optimal frame selection paths for different preloads by running the algorithm just once. We further extend the reverse frame selection algorithm to solve the problem of stored video delivery over bandwidth-limited and time-varying channels. MASTER OF ENGINEERING (SCE) 2008-09-17T09:03:46Z 2008-09-17T09:03:46Z 2007 2007 Thesis Tao, D.Y. (2012). Comparison of two methods of extracting carbohydrates from microalgae. Master’s thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/2465 10.32657/10356/2465 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
spellingShingle DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks
Tao, DaYong
Video adaptation for stored video delivery over resource-constrained networks
description This project studies content adaptation and bandwidth smoothing techniques for stored video delivery over resource-constrained networks. For the content adaptation approach, we apply the digital item adaptation standard defined in the MPEG-21 multimedia framework to maximize the bandwidth resource utilization and deliver the best quality video given the constraint user environment. The bandwidth smoothing approach presents an optimal frame selection algorithm under limited channel bandwidth and constrained client buffer condition. In addition, a novel reverse frame selection algorithm has been proposed that can find all the optimal frame selection paths for different preloads by running the algorithm just once. We further extend the reverse frame selection algorithm to solve the problem of stored video delivery over bandwidth-limited and time-varying channels.
author2 Cai Jianfei
author_facet Cai Jianfei
Tao, DaYong
format Theses and Dissertations
author Tao, DaYong
author_sort Tao, DaYong
title Video adaptation for stored video delivery over resource-constrained networks
title_short Video adaptation for stored video delivery over resource-constrained networks
title_full Video adaptation for stored video delivery over resource-constrained networks
title_fullStr Video adaptation for stored video delivery over resource-constrained networks
title_full_unstemmed Video adaptation for stored video delivery over resource-constrained networks
title_sort video adaptation for stored video delivery over resource-constrained networks
publishDate 2008
url https://hdl.handle.net/10356/2465
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