Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
research-article

An SDN Architecture for Privacy-Friendly Network-Assisted DASH

Published: 28 June 2017 Publication History

Abstract

Dynamic Adaptive Streaming over HTTP (DASH) is the premier technology for Internet video streaming. DASH efficiently uses existing HTTP-based delivery infrastructures implementing adaptive streaming. However, DASH traffic is bursty in nature. This causes performance problems when DASH players share a network connection or in networks with heavy background traffic. The result is unstable and lower quality video. In this article, we present the design and implementation of a so-called DASH Assisting Network Element (DANE). Our system provides target bitrate signaling and dynamic traffic control. These two mechanisms realize proper bandwidth sharing among clients. Our system is privacy friendly and fully supports encrypted video streams. Trying to improve the streaming experience for users who share a network connection, our system increases the video bitrate and reduces the number of quality switches. We show this through evaluations in our Wi-Fi testbed.

References

[1]
Saamer Akhshabi, Lakshmi Anantakrishnan, Ali C. Begen, and Constantine Dovrolis. 2012. What happens when HTTP adaptive streaming players compete for bandwidth? In Proceedings of the 22nd International Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV’12). ACM Request Permissions, New York, New York, 9--14.
[2]
Saamer Akhshabi, Ali C. Begen, and Constantine Dovrolis. 2011. An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In Proceedings of the 2nd Annual ACM Conference on Multimedia Systems. ACM, New York, NY, 157--168.
[3]
Niels Bouten, Jeroen Famaey, Steven Latré, Rafael Huysegems, B. D. Vleeschauwer, W. V. Leekwijck, and F. D. Turck. 2012. QoE optimization through in-network quality adaptation for HTTP adaptive streaming. In Network and Service Management (CNSM), 2012 8th International Conference and 2012 Workshop on Systems Virtualiztion Management (SVM). IEEE, 336--342.
[4]
Nicola Cranley, Philip Perry, and Liam Murphy. 2006. User perception of adapting video quality. International Journal of Human-Computer Studies 64, 8 (2006), 637--647.
[5]
Florin Dobrian, Asad Awan, Dilip Joseph, Aditya Ganjam, Jibin Zhan, Vyas Sekar, Ion Stoica, and Hui Zhang. 2013. Understanding the impact of video quality on user engagement. Commun. ACM 56, 3 (March 2013), 91--99.
[6]
Jairo Esteban, Steven A. Benno, Andre Beck, Yang Guo, Volker Hilt, and Ivica Rimac. 2012. Interactions between HTTP adaptive streaming and TCP. In Proceedings of the 22nd International Workshop on Network and Operating System Support for Digital Audio and Video. ACM, New York, NY, 21--26.
[7]
Panagiotis Georgopoulos, Yehia Elkhatib, Matthew Broadbent, Mu Mu, and Nicholas Race. 2013. Towards network-wide QoE fairness using openflow-assisted adaptive video streaming. In Proceedings of the 2013 ACM SIGCOMM Workshop on Future Human-centric Multimedia Networking (FhMN’13). ACM Request Permissions, New York, New York, 15--20.
[8]
Roelof Hamberg and Huib de Ridder. 1999. Time-varying image quality: Modeling the relation between instantaneous and overall quality. SMPTE Journal 108, 11 (1999), 802--811.
[9]
Tobias Hoßfeld, Michael Seufert, Christian Sieber, Thomas Zinner, and Phuoc Tran-Gia. 2015. Identifying QoE optimal adaptation of HTTP adaptive streaming based on subjective studies. Computer Networks 81 (2015), 320--332.
[10]
Rémi Houdaille and Stéphane Gouache. 2012. Shaping HTTP adaptive streams for a better user experience. In Proceedings of the 3rd Multimedia Systems Conference (MMSys’12). ACM Request Permissions, New York, New York, 1--9.
[11]
Te-Yuan Huang, Nikhil Handigol, Brandon Heller, Nick McKeown, and Ramesh Johari. 2012. Confused, timid, and unstable: Picking a video streaming rate is hard. In Proceedings of the 2012 ACM Conference on Internet Measurement Conference (IMC’12). ACM Request Permissions, New York, New York, 225--238.
[12]
ISO/IEC 23009-1. 2014. Information technology — Dynamic adaptive streaming over HTTP (DASH) — Part 1: Media presentation description and segment formats. 2nd edition (May 2014).
[13]
Dmitri Jarnikov and Tanır Özçelebi. 2011. Client intelligence for adaptive streaming solutions. Signal Processing: Image Communication 26, 7 (2011), 378--389.
[14]
Junchen Jiang, Vyas Sekar, and Hui Zhang. 2012. Improving fairness, efficiency, and stability in HTTP-based adaptive video streaming with FESTIVE. In Proceedings of the 8th International Conference on Emerging Networking Experiments and Technologies (CoNEXT’12). ACM Request Permissions, New York, New York, 97--108.
[15]
Jan Willem Kleinrouweler, Sergio Cabrero, and Pablo Cesar. 2016. Delivering stable high-quality video: An SDN architecture with DASH assisting network elements. In Proceedings of the 7th International Conference on Multimedia Systems (MMSys’16). ACM, New York, NY, Article 4, 10 pages.
[16]
Jan Willem Kleinrouweler, Sergio Cabrero, Rob van der Mei, and Pablo Cesar. 2015. Modeling stability and bitrate of network-assisted HTTP adaptive streaming players. In Proceedings of the 27th International Teletraffic Congress (ITC 27).
[17]
Stefan Lederer. 2015. Why YouTube 8 Netflix use MPEG-DASH in HTML5. Retrieved from https://bitmovin.com/status-mpeg-dash-today-youtube-netflix-use-html5-beyond/.
[18]
Chenghao Liu, Imed Bouazizi, and Moncef Gabbouj. 2011. Rate adaptation for adaptive HTTP streaming. In Proceedings of the 2nd Annual ACM Conference on Multimedia Systems. ACM, 169--174.
[19]
Nick McKeown, Tom Anderson, Hari Balakrishnan, Guru Parulkar, Larry Peterson, Jennifer Rexford, Scott Shenker, and Jonathan Turner. 2008. OpenFlow: Enabling innovation in campus networks. SIGCOMM Comput. Commun. Rev. 38, 2 (March 2008), 69--74.
[20]
Konstantin Miller, Emanuele Quacchio, Gianluca Gennari, and Adam Wolisz. 2012. Adaptation algorithm for adaptive streaming over HTTP. In Proceedings of the 19th International Packet Video Workshop (PV’12). IEEE, 173--178.
[21]
Stefano Petrangeli, Jeroen Famaey, Maxim Claeys, Steven Latré, and Filip De Turck. 2015. QoE-driven rate adaptation heuristic for fair adaptive video streaming. ACM Trans. Multimedia Comput. Commun. Appl. 12, 2 (Oct. 2015), 28:1--28:24.
[22]
David C. Robinson, Yves Jutras, and Viorel Craciun. 2012. Subjective video quality assessment of HTTP Adaptive Streaming Technologies. Bell Labs Technical Journal 16, 4 (2012), 5--23.
[23]
Sandvine, Inc. 2016. Global internet phenomena report: Latin America 8 North America (2016). https://www.sandvine.com/downloads/general/global-internet-phenomena/2016/global-internet-phenomena-report-latin-america-and-north-america.pdf (accessed 2017- 06- 13).
[24]
I. Sodagar. 2011. The MPEG-DASH standard for multimedia streaming over the internet. IEEE MultiMedia 18, 4 (Oct. 2011), 62--67.
[25]
Kevin Spiteri, Rahul Urgaonkar, and Ramesh K. Sitaraman. 2016. BOLA: Near-optimal bitrate adaptation for online videos. CoRR abs/1601.06748 (2016). http://arxiv.org/abs/1601.06748
[26]
E. Thomas, M. O. van Deventer, T. Stockhammer, A. C. Begen, and J. Famaey. 2015. Enhancing MPEG dash performance via server and network assistance. In The Best of IET and IBC. Institution of Engineering and Technology, 48--53.

Cited By

View all

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Multimedia Computing, Communications, and Applications
ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 13, Issue 3s
Special Section on Deep Learning for Mobile Multimedia and Special Section on Best Papers from ACM MMSys/NOSSDAV 2016
August 2017
258 pages
ISSN:1551-6857
EISSN:1551-6865
DOI:10.1145/3119899
Issue’s Table of Contents
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 the author(s) 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].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 June 2017
Accepted: 01 March 2017
Revised: 01 January 2017
Received: 01 September 2016
Published in TOMM Volume 13, Issue 3s

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. DASH
  2. HTTP adaptive streaming
  3. Wi-Fi
  4. network assistance
  5. performance
  6. video streaming

Qualifiers

  • Research-article
  • Research
  • Refereed

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)4
  • Downloads (Last 6 weeks)0
Reflects downloads up to 23 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)DiffPerf: Toward Performance Differentiation and Optimization With SDN ImplementationIEEE Transactions on Network and Service Management10.1109/TNSM.2023.329796621:1(1012-1031)Online publication date: 1-Feb-2024
  • (2022)An SDN-aided low-latency live video streaming over HTTPMultimedia Tools and Applications10.1007/s11042-022-12389-y81:16(23145-23162)Online publication date: 1-Jul-2022
  • (2020)PPNetACM Transactions on Multimedia Computing, Communications, and Applications10.1145/337998316:2(1-23)Online publication date: 22-May-2020
  • (2020)Performance issues and solutions in SDN-based data center: a surveyThe Journal of Supercomputing10.1007/s11227-020-03180-776:10(7545-7593)Online publication date: 30-Jan-2020
  • (2019)Chunk Duration--Aware SDN-Assisted DASHACM Transactions on Multimedia Computing, Communications, and Applications10.1145/333768115:3(1-22)Online publication date: 20-Aug-2019
  • (2019)MUCH: Priority-based Collaborative Multi-Channel HTTP Adaptive Streaming2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD)10.1109/CSCWD.2019.8791892(446-451)Online publication date: May-2019
  • (2018)ASAPACM Transactions on Multimedia Computing, Communications, and Applications10.1145/321975014:3s(1-23)Online publication date: 27-Jun-2018
  • (2017)Enhancing Over-the-Top Video Streaming Quality with DASH Assisting Network ElementsAdjunct Publication of the 2017 ACM International Conference on Interactive Experiences for TV and Online Video10.1145/3084289.3084295(113-116)Online publication date: 14-Jun-2017

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media