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A simple yet effective network-assisted signal for enhanced DASH quality of experience

Published:12 June 2018Publication History

ABSTRACT

We propose and evaluate simple signals coming from in-network telemetry that are effective to enhance the quality of DASH streaming. Specifically, in-network caching is known to positively affect DASH streaming quality but at the same time negatively affect the controller stability, increasing the quality switch ratio. Our contributions are to first (i) consider the broad spectrum of interaction between the network and the application, and then (ii) to devise how to effectively exploit in a DASH controller a very simple signal (i.e., per-quality hit ratio) that can be exported by framework such as Server and Network Assisted DASH (SAND) at fairly low rate (i.e., a timescale of 10s of seconds). Our thorough experimental campaign confirms the soundness of the approach (that significantly ameliorate performance with respect to network-blind DASH), as well as its robustness (i.e., tuning is not critical) and practical appeal (i.e., due to its simplicity and compatibility with SAND).

References

  1. https://newnet.telecom-paristech.fr/index.php/icn-das/.Google ScholarGoogle Scholar
  2. Cisco Visual Networking Index: Forecast and Methodology, 2016-2021, 2017.Google ScholarGoogle Scholar
  3. S. Akhshabi, S. Narayanaswamy, et al. An experimental evaluation of rate-adaptive video players over http. Signal Processing: Image Communication, 27(4):271, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. A. Bentaleb, A. Begen, et al. Sdndash: Improving qoe of http adaptive streaming using software defined networking. In ACM Multimedia (MM'16). 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Bhat, A. Rizk, et al. Network assisted content distribution for adaptive bitrate video streaming. In ACM on Multimedia Systems (MMSys'17). 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Bouten, N. et al. In-network quality optimization for adaptive video streaming services. IEEE Transactions on Multimedia, 16(8):2281, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  7. Cofano, G. et al. Design and experimental evaluation of network-assisted strategies for HTTP adaptive streaming. In ACM Multimedia Systems (MMSys). 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. S. D'Aronco, L. Toni, et al. Price-Based Controller for Utility-Aware HTTP Adaptive Streaming. IEEE MultiMedia, 24(2):20, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. F. Dobrian, A. Awan, et al. Understanding the impact of video quality on user engagement. Commun. ACM, 56(3):91, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Essaili, A.E. et al. QoE-based traffic and resource management for adaptive HTTP video delivery in LTE. IEEE Transactions on Circuits and Systems for Video Technology, 25(6):988, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  11. A. Ganjam, F. Siddiqui, et al. C3: Internet-scale control plane for video quality optimization. In USENIX NSDI. 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Georgopoulos, P. et al. Towards Network-wide QoE Fairness Using Openflow-assisted Adaptive Video Streaming. In ACM SIGCOMM, FhMN Workshop. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. R. Grandl, K. Su, et al. On the interaction of adaptive video streaming with content-centric networking. In International Packet Video Workshop (PV). 2013.Google ScholarGoogle ScholarCross RefCross Ref
  14. T. Y. e. a. Huang. A buffer-based approach to rate adaptation: Evidence from a large video streaming service. In Proc. of ACM SIGCOMM, pages 187--198. 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. R. Jmal, G. Simon, et al. Network-assisted strategy for DASH over CCN. In IEEE International Conference on Multimedia and Expo (ICME). 2017.Google ScholarGoogle ScholarCross RefCross Ref
  16. T. Karagkioules, C. Concolato, et al. A comparative case study of http adaptive streaming algorithms in mobile networks. In NOSSDAV, pages 1--6. ACM, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Kleinrouweler, S. Cabrero, et al. Delivering stable high-quality video: an SDN architecture with DASH assisting network elements. In ACM Multimedia Systems (MMSys). 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. D. Lee, C. Dovrolis, et al. Caching in http adaptive streaming: Friend or foe? In ACM NOSSDAV. 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. W. Li, S. M. A. Oteafy, et al. Dynamic adaptive streaming over popularity-driven caching in information-centric networks. In IEEE ICC. 2015.Google ScholarGoogle Scholar
  20. Mok, R.K.P. et al. QDASH: a QoE-aware DASH system. In ACM Multimedia Systems (MMSys). 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. M. K. Mukerjee, D. Naylor, et al. Practical, real-time centralized control for cdn-based live video delivery. In ACM SIGCOMM. 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. H. Nam, K. H. Kim, et al. Towards QoE-aware video streaming using SDN. In IEEE GLOBECOM. 2014.Google ScholarGoogle Scholar
  23. Posch, D. et al. Using In-Network Adaptation to Tackle Inefficiencies Caused by DASH in Information-Centric Networks. In Proc. of ACM VideoNext Workshop. 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. B. Rainer, D. Posch, et al. Investigating the Performance of Pull-based Dynamic Adaptive Streaming in NDN. Journal on Selected Areas in Communications, 34(8):2130, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. S. Schwarzmann, T. Zinner, et al. Towards a framework for comparing application-network interaction mechanisms. In Proc. of IEEE ITC 28. 2016.Google ScholarGoogle ScholarCross RefCross Ref
  26. The Linux Foundation. Fast Data project (fd.io) Community ICN (CICN). https://wiki.fd.io/view/Cicn, 2017.Google ScholarGoogle Scholar
  27. E. Thomas, T. Deventer, M.O. ad van Stockhammer, et al. Enhancing mpeg dash performance via server and network assistance. In Proceedings of IET and IBC, pages 48--53. IET, 2015.Google ScholarGoogle Scholar

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      • Published in

        cover image ACM Conferences
        NOSSDAV '18: Proceedings of the 28th ACM SIGMM Workshop on Network and Operating Systems Support for Digital Audio and Video
        June 2018
        84 pages
        ISBN:9781450357722
        DOI:10.1145/3210445

        Copyright © 2018 ACM

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        Publication History

        • Published: 12 June 2018

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