Reza Farahani
Farzad Tashtarian
Alireza Erfanian
Christian Timmerer
ABSTRACT
Recently, HTTP Adaptive Streaming (HAS) has become the dominant video delivery technology over the Internet. In HAS, clients have full control over the media streaming and adaptation processes. Lack of coordination among the clients and lack of awareness of the network conditions may lead to sub-optimal user experience and resource utilization in a pure client-based HAS adaptation scheme. Software Defined Networking (SDN) has recently been considered to enhance the video streaming process. In this paper, we leverage the capability of SDN and Network Function Virtualization (NFV) to introduce an edge- and SDN-assisted video streaming framework called ES-HAS. We employ virtualized edge components to collect HAS clients' requests and retrieve networking information in a time-slotted manner. These components then perform an optimization model in a time-slotted manner to efficiently serve clients' requests by selecting an optimal cache server (with the shortest fetch time). In case of a cache miss, a client's request is served (i) by an optimal replacement quality (only better quality levels with minimum deviation) from a cache server, or (ii) by the original requested quality level from the origin server. This approach is validated through experiments on a large-scale testbed, and the performance of our framework is compared to pure client-based strategies and the SABR system [12]. Although SABR and ES-HAS show (almost) identical performance in the number of quality switches, ES-HAS outperforms SABR in terms of playback bitrate and the number of stalls by at least 70% and 40%, respectively.
- 2007. MongoDB. Retrieved 2021-03-07 from https://www.mongodb.comGoogle Scholar
- 2012. Floodlight. Retrieved 2021-03-07 from https://github.com/floodlight/floodlightGoogle Scholar
- 2013. AStream: A rate adaptation model for DASH. Retrieved 2021-03-07 from https://github.com/pari685/AStreamGoogle Scholar
- 2020. Apache HTTP Server. Retrieved 2021-03-07 from https://httpd.apache.orgGoogle Scholar
- 2020. PuLP. Retrieved 2021-04-13 from https://pypi.org/project/PuLP/Google Scholar
- 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. 9--14.Google ScholarDigital Library
- Alcardo Alex Barakabitze, Arslan Ahmad, Rashid Mijumbi, and Andrew Hines. 2020. 5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges. Computer Networks 167 (2020), 106984.Google ScholarDigital Library
- Alcardo Alex Barakabitze, Nabajeet Barman, Arslan Ahmad, Saman Zadtootaghaj, Lingfen Sun, Maria G Martini, and Luigi Atzori. 2019. QoE management of multimedia streaming services in future networks: a tutorial and survey. IEEE Communications Surveys & Tutorials (2019).Google Scholar
- Abdelhak Bentaleb, Ali C Begen, and Roger Zimmermann. 2016. SDNDASH: Improving QoE of HTTP adaptive streaming using software defined networking. In Proceedings of the 24th ACM International Conference on Multimedia. 1296--1305.Google ScholarDigital Library
- Abdelhak Bentaleb, Ali C Begen, Roger Zimmermann, and Saad Harous. 2017. SDNHAS: An SDN-enabled architecture to optimize QoE in HTTP adaptive streaming. IEEE Transactions on Multimedia 19, 10 (2017), 2136--2151.Google ScholarDigital Library
- Abdelhak Bentaleb, Bayan Taani, Ali C Begen, Christian Timmerer, and Roger Zimmermann. 2018. A survey on bitrate adaptation schemes for streaming media over HTTP. IEEE Communications Surveys & Tutorials 21, 1 (2018), 562--585.Google ScholarCross Ref
- Divyashri Bhat, Amr Rizk, Michael Zink, and Ralf Steinmetz. 2017. Network assisted content distribution for adaptive bitrate video streaming. In Proceedings of the 8th ACM on Multimedia Systems Conference. 62--75.Google ScholarDigital Library
- Margaret Chiosi, Don Clarke, Peter Willis, Andy Reid, James Feger, Michael Bugenhagen, Waqar Khan, Michael Fargano, Chunfeng Cui, Hui Deng, et al. 2012. Network functions virtualisation: An introduction, benefits, enablers, challenges and call for action. In SDN and OpenFlow World Congress, Vol. 48. SN, 202.Google Scholar
- Cisco. February 2019. Cisco Visual Networking Index: Forecast and Trends, 2017--2022. White Paper (February 2019).Google Scholar
- Consumer Technology Association. 2020. CTA Specification: Web Application Video Ecosystem - Common Media Client Data. CTA-5004. Technical Report. https://cdn.cta.tech/cta/media/media/resources/standards/pdfs/cta-5004-final.pdfGoogle Scholar
- Oussama El Marai, Tarik Taleb, Mohamed Menacer, and Mouloud Koudil. 2017. On improving video streaming efficiency, fairness, stability, and convergence time through client-server cooperation. IEEE Transactions on Broadcasting 64, 1 (2017), 11--25.Google ScholarCross Ref
- Alireza Erfanian, Farzad Tashtarian, Reza Farahani, Christian Timmerer, and Hermann Hellwagner. 2020. On Optimizing Resource Utilization in AVC-based Real-time Video Streaming. In 2020 6th IEEE Conference on Network Softwarization (NetSoft). IEEE, 301--309.Google Scholar
- Alireza Erfanian, Farzad Tashtarian, and Mohammad H. Yaghmaee. 2018. On Maximizing QoE in AVC-Based HTTP Adaptive Streaming: An SDN Approach. In 2018 IEEE/ACM 26th International Symposium on Quality of Service (IWQoS). 1--10. Google ScholarCross Ref
- 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 Internet Measurement conference. 225--238.Google ScholarDigital Library
- 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. 97--108.Google ScholarDigital Library
- Parikshit Juluri, Venkatesh Tamarapalli, and Deep Medhi. 2015. SARA: Segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP. In 2015 IEEE International Conference on Communication Workshop (ICCW). IEEE, 1765--1770.Google ScholarCross Ref
- Diego Kreutz, Fernando MV Ramos, Paulo Esteves Verissimo, Christian Esteve Rothenberg, Siamak Azodolmolky, and Steve Uhlig. 2014. Software-defined networking: A comprehensive survey. Proc. IEEE 103, 1 (2014), 14--76.Google ScholarCross Ref
- Stefan Lederer, Christopher Müller, and Christian Timmerer. 2012. Dynamic adaptive streaming over HTTP dataset. In Proceedings of the 3rd Multimedia Systems Conference. 89--94.Google ScholarDigital Library
- Hwanwook Lee, Yunmin Go, and Hwangjun Song. 2018. SDN-assisted HTTP adaptive streaming over Wi-Fi network. In 2018 Fifth International Conference on Software Defined Systems (SDS). IEEE, 205--210.Google ScholarCross Ref
- Zhi Li, Xiaoqing Zhu, Joshua Gahm, Rong Pan, Hao Hu, Ali C Begen, and David Oran. 2014. Probe and adapt: Rate adaptation for HTTP video streaming at scale. IEEE Journal on Selected Areas in Communications 32, 4 (2014), 719--733.Google ScholarCross Ref
- Konstantin Miller, Emanuele Quacchio, Gianluca Gennari, and Adam Wolisz. 2012. Adaptation algorithm for adaptive streaming over HTTP. In 2012 19th International Packet Video Workshop (PV). IEEE, 173--178.Google ScholarCross Ref
- Robert Ricci, Eric Eide, and CloudLab Team. 2014. Introducing CloudLab: Scientific infrastructure for advancing cloud architectures and applications. ; login:: the magazine of USENIX & SAGE 39, 6 (2014), 36--38.Google Scholar
- Iraj Sodagar. 2011. The MPEG-DASH standard for multimedia streaming over the internet. IEEE Multimedia 18, 4 (2011), 62--67.Google ScholarDigital Library
- Kevin Spiteri, Rahul Urgaonkar, and Ramesh K Sitaraman. 2016. BOLA: Near-optimal bitrate adaptation for online videos. In IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications. IEEE, 1--9.Google ScholarDigital Library
- Emmanuel Thomas, MO van Deventer, Thomas Stockhammer, Ali C Begen, M-L Champel, and Ozgur Oyman. 2016. Applications and deployments of server and network assisted DASH (SAND). (2016).Google Scholar
- Cong Wang, Amr Rizk, and Michael Zink. 2016. SQUAD: A spectrum-based quality adaptation for dynamic adaptive streaming over HTTP. In Proceedings of the 7th International Conference on Multimedia Systems. 1--12.Google ScholarDigital Library
Index Terms
- ES-HAS: an edge- and SDN-assisted framework for HTTP adaptive video streaming
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