research-article

iDASH: improved dynamic adaptive streaming over HTTP using scalable video coding

Authors:

Yago Sánchez de la Fuente,

Danny De Vleeschauwer,

Werner Van Leekwijck,

Yannick Le LouédecAuthors Info & Claims

MMSys '11: Proceedings of the second annual ACM conference on Multimedia systems

Pages 257 - 264

https://doi.org/10.1145/1943552.1943586

Published: 23 February 2011 Publication History

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Abstract

HTTP-based delivery for Video on Demand (VoD) has been gaining popularity within recent years. Progressive Download over HTTP, typically used in VoD, takes advantage of the widely deployed network caches to relieve video servers from sending the same content to a high number of users in the same access network. However, due to a sharp increase in the requests at peak hours or due to cross-traffic within the network, congestion may arise in the cache feeder link or access link respectively. Since the connection characteristics may vary over the time, with Dynamic Adaptive Streaming over HTTP (DASH), a technique that has been recently proposed, video clients may dynamically adapt the requested video quality for ongoing video flows, to match their current download rate as good as possible. In this work we show the benefits of using the Scalable Video Coding (SVC) for such a DASH environment.

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References

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Cited By

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Nie LYang SZheng XWang X(2023)An Efficient and Adaptive Content Delivery System Based on Hybrid NetworkIEEE Transactions on Broadcasting10.1109/TBC.2023.330171669:4(904-915)Online publication date: Dec-2023
https://doi.org/10.1109/TBC.2023.3301716
Gohar ALee S(2020)Multipath Dynamic Adaptive Streaming over HTTP Using Scalable Video Coding in Software Defined NetworkingApplied Sciences10.3390/app1021769110:21(7691)Online publication date: 30-Oct-2020
https://doi.org/10.3390/app10217691
Fei TGong QDingt W(2020)An edge-caching algorithm based on fine-grained SVC for video streaming2020 7th International Conference on Information Science and Control Engineering (ICISCE)10.1109/ICISCE50968.2020.00055(219-223)Online publication date: Dec-2020
https://doi.org/10.1109/ICISCE50968.2020.00055
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Index Terms

iDASH: improved dynamic adaptive streaming over HTTP using scalable video coding
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies

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Information

Published In

MMSys '11: Proceedings of the second annual ACM conference on Multimedia systems

February 2011

294 pages

ISBN:9781450305181

DOI:10.1145/1943552

General Chairs:
Ali C. Begen
Cisco, Canada
,
Ketan Mayer-Patel
University of North Carolina, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 February 2011

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MMSYS '11: MMSYS '11 - Multimedia Systems Conference

February 23 - 25, 2011

CA, San Jose, USA

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Overall Acceptance Rate 176 of 530 submissions, 33%

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Nie LYang SZheng XWang X(2023)An Efficient and Adaptive Content Delivery System Based on Hybrid NetworkIEEE Transactions on Broadcasting10.1109/TBC.2023.330171669:4(904-915)Online publication date: Dec-2023
https://doi.org/10.1109/TBC.2023.3301716
Gohar ALee S(2020)Multipath Dynamic Adaptive Streaming over HTTP Using Scalable Video Coding in Software Defined NetworkingApplied Sciences10.3390/app1021769110:21(7691)Online publication date: 30-Oct-2020
https://doi.org/10.3390/app10217691
Fei TGong QDingt W(2020)An edge-caching algorithm based on fine-grained SVC for video streaming2020 7th International Conference on Information Science and Control Engineering (ICISCE)10.1109/ICISCE50968.2020.00055(219-223)Online publication date: Dec-2020
https://doi.org/10.1109/ICISCE50968.2020.00055
Yu L(2020)SVC-based dynamic caching for smart media streaming over the Internet of ThingsFuture Generation Computer Systems10.1016/j.future.2020.06.042Online publication date: Jul-2020
https://doi.org/10.1016/j.future.2020.06.042
MORI SBANDAI M(2019)A Quality-Level Selection for Adaptive Video Streaming with Scalable Video CodingIEICE Transactions on Communications10.1587/transcom.2017EBP3432E102.B:4(824-831)Online publication date: 1-Apr-2019
https://doi.org/10.1587/transcom.2017EBP3432
Friedlander EAggarwal V(2019)Generalization of LRU Cache Replacement Policy with Applications to Video StreamingACM Transactions on Modeling and Performance Evaluation of Computing Systems10.1145/33450224:3(1-22)Online publication date: 20-Aug-2019
https://dl.acm.org/doi/10.1145/3345022
Gong QWoods JKar KChakareski J(2019)Multiple-Cache Pairing for Fine-Grained Scalable Video Caching and NetworkingProceedings of the 14th International Conference on Future Internet Technologies10.1145/3341188.3341196(1-7)Online publication date: 7-Aug-2019
https://dl.acm.org/doi/10.1145/3341188.3341196
Gohar ARaza ALee S(2019)Dynamic Adaptive Streaming Over HTTP Using Scalable Video Coding with Multipath TCP in SDN2019 International Conference on Information Networking (ICOIN)10.1109/ICOIN.2019.8718153(480-484)Online publication date: Jan-2019
https://doi.org/10.1109/ICOIN.2019.8718153
Ozcan SSayit M(2019)Improving the QoE of DASH over SDN: A MCDM Method with an Intelligent Approach2019 22nd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)10.1109/ICIN.2019.8685903(100-105)Online publication date: Feb-2019
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Hosseini SPanwar S(2019)Restless Video Bandits: Optimal SVC Streaming in a Multi-User Wireless NetworkIEEE Access10.1109/ACCESS.2019.29479027(150805-150822)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2947902
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Tune to Lambda patching

Sharing Multicast Videos Using Patching Streams

QoE Driven Server Selection for VoD in the Cloud

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