research-article

Evaluation of HTTP-based request-response streams for internet video streaming

Authors:

Robert Kuschnig,

Hermann HellwagnerAuthors Info & Claims

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

Pages 245 - 256

https://doi.org/10.1145/1943552.1943585

Published: 23 February 2011 Publication History

Abstract

Adaptive video streaming based on TCP/HTTP is becoming popular because of its ability to adapt to changing network conditions. We present an in-depth experimental analysis of the use of HTTP-based request-response streams for video streaming. In this scheme, video fragments are fetched by a client from the server, in smaller units called chunks, potentially via multiple parallel HTT P requests (TCP connections). A model for the achievable throughput is formulated.The model is validated by a broad range of streaming experiments, including an evaluation of TCP-friendliness.

Our findings include that request-response streams are able to scale with the available bandwidth by increasing the chunk size or the number of concurrent streams. Several combinations of system parameters exhibiting TCP-friendliness are presented. We also evaluate the video streaming performance in terms of video quality in the presence of packet loss. Multiple request-response streams are able to maintain satisfactory performance, while a single TCP connection deteriorates rapidly with increasing packet loss. The results provide experimental evidence that HTTP-based request-response streams are a good alternative to classical TCP streaming

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Cited By

Hwang MPark JChung K(2020)Dynamic Block-Based HTTP Adaptive Streaming Scheme in Multiple Wireless NetworksIEEE Access10.1109/ACCESS.2020.30119408(138447-138455)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3011940
Quinlan JZahran ASreenan C(2018)Efficient Delivery of Scalable Video Using a Streaming Class ModelInformation10.3390/info90300599:3(59)Online publication date: 8-Mar-2018
https://doi.org/10.3390/info9030059
Ozfatura EErcetin OInaltekin H(2018)Optimal Network-Assisted Multiuser DASH Video StreamingIEEE Transactions on Broadcasting10.1109/TBC.2018.282364464:2(247-265)Online publication date: Jun-2018
https://doi.org/10.1109/TBC.2018.2823644
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Index Terms

Evaluation of HTTP-based request-response streams for internet video streaming
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

cover image ACM Conferences

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

Copyright © 2011 ACM.

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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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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Cited By

Hwang MPark JChung K(2020)Dynamic Block-Based HTTP Adaptive Streaming Scheme in Multiple Wireless NetworksIEEE Access10.1109/ACCESS.2020.30119408(138447-138455)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3011940
Quinlan JZahran ASreenan C(2018)Efficient Delivery of Scalable Video Using a Streaming Class ModelInformation10.3390/info90300599:3(59)Online publication date: 8-Mar-2018
https://doi.org/10.3390/info9030059
Ozfatura EErcetin OInaltekin H(2018)Optimal Network-Assisted Multiuser DASH Video StreamingIEEE Transactions on Broadcasting10.1109/TBC.2018.282364464:2(247-265)Online publication date: Jun-2018
https://doi.org/10.1109/TBC.2018.2823644
Kim YChung K(2018)Multipath-based transmission scheme for improving the QoE of HTTP adaptive streamingJournal of Visual Communication and Image Representation10.1016/j.jvcir.2018.05.01755(12-20)Online publication date: Aug-2018
https://doi.org/10.1016/j.jvcir.2018.05.017
Karn NZhang HJiang F(2018)User-perceived quality aware adaptive streaming of 3D multi-view video plus depth over the internetMultimedia Tools and Applications10.1007/s11042-018-5744-877:17(22965-22983)Online publication date: 1-Sep-2018
https://dl.acm.org/doi/10.1007/s11042-018-5744-8
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https://dl.acm.org/doi/10.1145/3126517
Mehrabian MKhayatian MShrivastava AEidson JDerler PAndrade HLi-Baboud YGriffor EWeiss MStanton K(2017)Timestamp Temporal Logic (TTL) for Testing the Timing of Cyber-Physical SystemsACM Transactions on Embedded Computing Systems10.1145/312651016:5s(1-20)Online publication date: 27-Sep-2017
https://dl.acm.org/doi/10.1145/3126510
Schulze CCleaveland R(2017)Improving Invariant Mining via Static AnalysisACM Transactions on Embedded Computing Systems10.1145/312650416:5s(1-20)Online publication date: 27-Sep-2017
https://dl.acm.org/doi/10.1145/3126504
Li XCheung MShe J(2017)A Distributed Streaming Framework for Connection Discovery Using Shared VideosACM Transactions on Multimedia Computing, Communications, and Applications10.1145/312099613:4(1-24)Online publication date: 18-Sep-2017
https://dl.acm.org/doi/10.1145/3120996
Dang-Nguyen DPiras LGiacinto GBoato GNatale F(2017)Multimodal Retrieval with Diversification and Relevance Feedback for Tourist Attraction ImagesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/310361313:4(1-24)Online publication date: 12-Aug-2017
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