skip to main content
10.1145/1943552.1943574acmconferencesArticle/Chapter ViewAbstractPublication PagesmmsysConference Proceedingsconference-collections
research-article

An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP

Published: 23 February 2011 Publication History
  • Get Citation Alerts
  • Abstract

    Adaptive (video) streaming over HTTP is gradually being adopted, as it offers significant advantages in terms of both user-perceived quality and resource utilization for content and network service providers. In this paper, we focus on the rate-adaptation mechanisms of adaptive streaming and experimentally evaluate two major commercial players (Smooth Streaming, Netflix) and one open source player (OSMF). Our experiments cover three important operating conditions. First, how does an adaptive video player react to either persistent or short-term changes in the underlying network available bandwidth. Can the player quickly converge to the maximum sustainable bitrate? Second, what happens when two adaptive video players compete for available bandwidth in the bottleneck link? Can they share the resources in a stable and fair manner? And third, how does adaptive streaming perform with live content? Is the player able to sustain a short playback delay? We identify major differences between the three players, and significant inefficiencies in each of them.

    Supplementary Material

    MP4 File (110224_26192_04_acm.mp4)

    References

    [1]
    Adobe. HTTP Dynamic Streaming on the Adobe Flash Platform. Adobe Systems Incorporated, 2010. http://www.adobe.com/products/httpdynamicstreaming /pdfs/httpdynamicstreaming_wp_ue.pdf.
    [2]
    A. C. Begen, T. Akgul, and M. Baugher. Watching video over the Web, part I: streaming protocols. To appear in IEEE Internet Comput., 2011.
    [3]
    L. De Cicco and S. Mascolo. An Experimental Investigation of the Akamai Adaptive Video Streaming. In Proc. of USAB WIMA, 2010.
    [4]
    S. Deshpande. Adaptive timeline aware client controlled HTTP streaming. In Proc. of SPIE, 2009.
    [5]
    W. Feng, M. Liu, B. Krishnaswami, and A. Prabhudev. A priority-based technique for the best-effort delivery of stored video. In Proc. of MMCN, 1999.
    [6]
    R. Gao, C. Dovrolis, and E. Zegura. Avoiding oscillations due to intelligent route control systems. In Proc. of IEEE INFOCOM, 2006.
    [7]
    A. Goel, C. Krasic, and J. Walpole. Low-latency adaptive streaming over TCP. ACM TOMCCAP, 4(3):1--20, 2008.
    [8]
    P.-H. Hsiao, H. T. Kung, and K.-S. Tan. Video over TCP with receiver-based delay control. In Proc. of ACM NOSSDAV, 2001.
    [9]
    R. Kuschnig, I. Kofler, and H. Hellwagner. An evaluation of TCP-based rate-control algorithms for adaptive Internet streaming of H.264/SVC. In Proc. of ACM MMSys, 2010.
    [10]
    R. Kuschnig, I. Kofler, and H. Hellwagner. Improving Internet video streamilng performance by parallel TCP-based request-response streams. In Proc. of IEEE CCNC, 2010.
    [11]
    Pomelo LLC. Analysis of Netflix's security framework for 'Watch Instantly' service. Pomelo, LLC Tech Memo, 2009. http://pomelollc.files.wordpress. com/2009/04/pomelo-tech-report-netflix.pdf.
    [12]
    A. Orebaugh, G. Ramirez, J. Burke, and J. Beale. Wireshark and Ethereal network protocol analyzer toolkit. Syngress Media Inc, 2007.
    [13]
    M. Prangl, I. Kofler, and H. Hellwagner. Towards QoS improvements of TCP-based media delivery. In Proc. of ICNS, 2008.
    [14]
    L. Rizzo. Dummynet: a simple approach to the evaluation of network protocols. SIGCOMM CCR, 27(1):31--41, 1997.
    [15]
    S. Tullimas, T. Nguyen, R. Edgecomb, and S.-C. Cheung. Multimedia streaming using multiple TCP connections. ACM TOMCCAP, 4(2):1--20, 2008.
    [16]
    B. Wang, J. Kurose, P. Shenoy, and D. Towsley. Multimedia streaming via TCP: An analytic performance study. ACM TOMCCAP, 4(2):1--22, 2008.
    [17]
    A. Zambelli. IIS smooth streaming technical overview. Microsoft Corporation, 2009. http://download.microsoft.com/download/4/2/4/ 4247C3AA-7105-4764-A8F9-321CB6C765EB/IIS_ Smooth_Streaming_Technical_Overview.pdf.

    Cited By

    View all
    • (2024)Real-EVE: Real-Time Edge-Assist Video Enhancement for Joint Denoising and Super-ResolutionAlgorithms and Architectures for Parallel Processing10.1007/978-981-97-0834-5_19(320-339)Online publication date: 12-Mar-2024
    • (2023)TASQ: Temporal Adaptive Streaming over QUICProceedings of the 14th Conference on ACM Multimedia Systems10.1145/3587819.3590991(194-204)Online publication date: 7-Jun-2023
    • (2023)Concerto: Client-server Orchestration for Real-Time Video AnalyticsProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3611770(9215-9223)Online publication date: 26-Oct-2023
    • Show More Cited By

    Recommendations

    Comments

    Information & Contributors

    Information

    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
    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]

    Sponsors

    In-Cooperation

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 23 February 2011

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. adaptive streaming
    2. experimental evaluation
    3. rate adaptation algorithm
    4. video streaming over http

    Qualifiers

    • Research-article

    Conference

    MMSYS '11
    Sponsor:
    MMSYS '11: MMSYS '11 - Multimedia Systems Conference
    February 23 - 25, 2011
    CA, San Jose, USA

    Acceptance Rates

    Overall Acceptance Rate 176 of 530 submissions, 33%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)48
    • Downloads (Last 6 weeks)2

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Real-EVE: Real-Time Edge-Assist Video Enhancement for Joint Denoising and Super-ResolutionAlgorithms and Architectures for Parallel Processing10.1007/978-981-97-0834-5_19(320-339)Online publication date: 12-Mar-2024
    • (2023)TASQ: Temporal Adaptive Streaming over QUICProceedings of the 14th Conference on ACM Multimedia Systems10.1145/3587819.3590991(194-204)Online publication date: 7-Jun-2023
    • (2023)Concerto: Client-server Orchestration for Real-Time Video AnalyticsProceedings of the 31st ACM International Conference on Multimedia10.1145/3581783.3611770(9215-9223)Online publication date: 26-Oct-2023
    • (2023)Is IPFS Ready for Decentralized Video Streaming?Proceedings of the ACM Web Conference 202310.1145/3543507.3583404(3002-3010)Online publication date: 30-Apr-2023
    • (2023)Adaptive Video Streaming With Automatic Quality-of-Experience OptimizationIEEE Transactions on Mobile Computing10.1109/TMC.2022.316135122:8(4456-4470)Online publication date: 1-Aug-2023
    • (2023)Fused image robust video watermarking technique using LWT, SVD and SWT2023 IEEE 3rd International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)10.1109/TEMSMET56707.2023.10149916(1-8)Online publication date: 10-Feb-2023
    • (2023)CANE: A Cascade Control Approach for Network-Assisted Video QoE ManagementIEEE Transactions on Control Systems Technology10.1109/TCST.2023.326771631:6(2543-2554)Online publication date: Nov-2023
    • (2022)Online Teaching Wireless Video Stream Resource Dynamic Allocation Method considering Node AbilityScientific Programming10.1155/2022/43911882022Online publication date: 1-Jan-2022
    • (2022)Machine Learning for Computer Systems and Networking: A SurveyACM Computing Surveys10.1145/352305755:4(1-36)Online publication date: 21-Nov-2022
    • (2022)AdaMask: Enabling Machine-Centric Video Streaming with Adaptive Frame Masking for DNN Inference OffloadingProceedings of the 30th ACM International Conference on Multimedia10.1145/3503161.3548033(3035-3044)Online publication date: 10-Oct-2022
    • Show More Cited By

    View Options

    Get Access

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media