Open Access
Subscription Access
QoE Evaluation of Legacy TCP Variants over DASH
Even though there is considerable work in adaptive video streaming, video players still suffer drawbacks which include: inadequate fair share, poor bandwidth utilization, frequent level shifts and high re-buffering ratios. These draw- backs result in poor perceived video quality which degrades a viewers quality of experience (QoE). DASH approaches have been known to deliver higher QoE to viewers by improving the video players segment selection. However, the transport layer protocol is another important aspect of video streaming. Hypertext Transfer Protocol (HTTP) is the most used application layer protocol over the Internet. It utilizes Transmission Control Protocol (TCP) as its transport layer protocol. TCP variants use different mechanisms for congestion control. The DASH standard uses HTTP, thus TCP variant selection becomes very important for effective video streaming. In this paper we test the performance of four linux-based TCP variants using the Conventional, PANDA and ELASTIC client-side DASH players in congested bottleneck link conditions. These experiments illustrate the varying impact on viewer QoE when using these various TCP congestion control mechanisms. The importance of TCP variant selection is exemplified as we observe that Westwood+ and YeAH are the most promising variants.
Keywords
QoE, DASH, HTTP, TCP, congestion, PANDA, ELASTIC, Westwood, YeAH.
User
Font Size
Information
- R. Rejaie, M. Handley, and D. Estrin, “Rap: An endto-end rate-based congestion control mechanism for realtime streams in the internet,” in INFOCOM’99.Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, vol. 3. IEEE, 1999, pp. 1337– 1345.
- M. Handley, S. Floyd, J. Padhye, and J. Widmer, “Tcp friendly rate control (tfrc): Protocol specification,” Tech. Rep., 2002.
- R. Fielding, J. Gettys, J. Mogul, H. Frystyk, L. Masinter, P. Leach, and T. Berners-Lee, “Hypertext transfer protocol–http/1.1,” Tech. Rep., 1999.
- J. Postel, “Transmission control protocol,” 1981.
- S. Guha and P. Francis, “Characterization and measurement of tcp traversal through nats and firewalls,” in Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement. USENIX Association, 2005, pp. 18–18.
- L. F. Sarmenta and S. Hirano, “Bayanihan: Building and studying web-based volunteer computing systems using java,” Future Generation Computer Systems, vol. 15, no. 5, pp. 675–686, 1999.
- C. Callegari, S. Giordano, M. Pagano, and T. Pepe, “Behavior analysis of tcplinux variants,” Computer Networks, vol. 56, no. 1, pp. 462–476, 2012.
- S. Mascolo, C. Casetti, M. Gerla, M. Y. Sanadidi, and R. Wang, “Tcpwestwood: Bandwidth estimation for enhanced transport over wireless links,” in Proceedings of the 7th annual international conference on Mobile computing and networking. ACM, 2001, pp. 287–297.
- S. Ha, I. Rhee, and L. Xu, “Cubic: a new tcp-friendly high-speed tcp variant,” ACM SIGOPS operating systems review, vol. 42, no. 5, pp. 64–74, 2008.
- A. Baiocchi, A. P. Castellani, and F. Vacirca, “Yeahtcp: yet another highspeed tcp,” in Proc. PFLDnet, vol. 7, 2007, pp. 37–42.
- S. Liu, T. Bas¸ar, and R. Srikant, “Tcp-illinois: A loss-and delay-based congestion control algorithm for high-speed networks,” Performance Evaluation, vol. 65, no. 6-7, pp. 417–440, 2008.
- K. Khan and W. Goodridge, “B-dash: broadcast-based dynamic adaptive streaming over http,” International Journal of Autonomous and Adaptive Communications Systems, vol. 12, no. 1, pp. 50–74, 2019.
- Khan, Koffka, and Wayne Goodridge. "S-mdp: Streaming with markov decision processes." IEEE Transactions on Multimedia 21, no. 8 (2019): 20122025.
- Z. Li, X. Zhu, J. Gahm, R. Pan, H. Hu, A. C. Begen, and D. Oran, “Probe and adapt: Rate adaptation for http video streaming at scale,” IEEE Journal on Selected Areas in Communications, vol. 32, no. 4, pp. 719–733, 2014.
- S. Sen, J. L. Rexford, J. K. Dey, J. F. Kurose, and D. F. Towsley, “Online smoothing of variable-bit-rate streaming video,” IEEE Transactions on Multimedia, vol. 2, no. 1, pp. 37–48, 2000.
- L. De Cicco, V. Caldaralo, V. Palmisano, and S. Mascolo, “Elastic: a client-side controller for dynamic adaptive streaming over http (dash),” in 2013 20th International Packet Video Workshop. IEEE, 2013, pp. 1–8.
- S. Barre,´ O. Bonaventure, C. Raiciu, and M. Handley, “Experimenting with multipath tcp,” ACM SIGCOMM Computer Communication Re-view, vol.41, no. 4, pp. 443–444, 2011.
- K. Khan and W. Goodridge, “Energy aware ad-hoc on demand multipath distance vector routing,” International Journal of Intelligent Systems and Applications, vol. 7, no. 7, pp. 50–56, 2015.
- M. Gerla, M. Y. Sanadidi, R. Wang, A. Zanella, C. Casetti, and S. Mas-colo, “Tcpwestwood: Congestion window control using bandwidth estimation,” in GLOBECOM’01. IEEE Global Telecommunications Con-ference (Cat. No. 01CH37270), vol. 3. IEEE, 2001, pp. 1698–1702.
- L. De Cicco, V. Caldaralo, V. Palmisano, and S. Mascolo, “Tapas: a tool for rapid prototyping of adaptive streaming algorithms,” in Proceedings of the 2014 Workshop on Design, Quality and Deployment of Adaptive Video Streaming. ACM, 2014, pp. 1–6.
- K. Khan and W. Goodridge, “Qoe evaluation of dynamic adaptive streaming over http (dash) with promising transport layer protocols,” CCF Transactions on Networking, pp. 1–16, 2020.
- M. Obrist, P. Cesar, D. Geerts, T. Bartindale, and E. F. Churchill, “Online video and interactive tv experiences,” interactions, vol. 22, no. 5, pp. 32–37, 2015.
- A. McZeal Jr, “Multifunctional world wide walkie talkie, a tri-frequency cellular-satellite wireless instant messenger computer and network for establishing global wireless volp quality of service (qos) communica-tions, unified messaging, and video conferencing via the internet,” Jul. 13 2004, uS Patent 6,763,226.
- A. Balachandran, V. Sekar, A. Akella, S. Seshan, I. Stoica, and H. Zhang, “Developing a predictive model of quality of experience for internet video,” in ACM SIGCOMM Computer Communication Review, vol. 43, no. 4. ACM, 2013, pp. 339–350.
- T. Hoßfeld, R. Schatz, E. Biersack, and L. Plissonneau, “Internet video delivery in youtube: From traffic measurements to quality of experience,” in Data Traffic Monitoring and Analysis. Springer, 2013, pp. 264–301.
- P. Brooks and B. Hestnes, “User measures of quality of experience: why being objective and quantitative is important,” IEEE network, vol. 24, no. 2, pp. 8–13, 2010.
- K. U. R. Laghari and K. Connelly, “Toward total quality of experience: A qoe model in a communication ecosystem,” IEEE Communications Magazine, vol. 50, no. 4, pp. 58–65, 2012.
- A. Takahashi, D. Hands, and V. Barriac, “Standardization activities in the itu for a qoe assessment of iptv,” IEEE Communications Magazine, vol. 46, no. 2, pp. 78–84, 2008.
- S. Tavakoli, K. Brunnstrom,¨ J. Gutierrez,´ and N. Garc´ıa, “Quality of experience of adaptive video streaming: investigation in service parame-ters and subjective quality assessment methodology,” Signal Processing: Image Communication, vol. 39, pp. 432– 443, 2015.
- M. T. Vega, C. Perra, F. De Turck, and A. Liotta, “A review of predictive quality of experience management in video streaming services,” IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 432– 445, 2018.
- Y. Chen, K. Wu, and Q. Zhang, “From qos to qoe: A tutorial on video quality assessment,” IEEE Communications Surveys & Tutorials, vol. 17, no. 2, pp. 1126–1165, 2014.
- N. Eswara, S. Chakraborty, H. P. Sethuram, K. Kuchi, A. Kumar, and S. Channappayya, “Perceptual qoeoptimal resource allocation for adaptive video streaming,” IEEE Transactions on Broadcasting, vol. 66, no. 2, pp. 346–358, 2019.
- M. Seufert, “Fundamental advantages of considering quality of experi-ence distributions over mean opinion scores,” in 2019 Eleventh Inter-national Conference on Quality of Multimedia Experience (QoMEX). IEEE, 2019, pp. 1–6.
- Q. Huynh-Thu and M. Ghanbari, “Scope of validity of psnr in im-age/video quality assessment,” Electronics letters, vol. 44, no. 13, pp. 800–801, 2008.
- D. M. Allen, “Mean square error of prediction as a criterion for selecting variables,” Technometrics, vol. 13, no. 3, pp. 469–475, 1971.
- A. Martin, J. Egana,˜ J. Florez,´ J. Montalban,´ I. G. Olaizola, M. Quartulli,Viola, and M. Zorrilla, “Network resource allocation system for qoe-aware delivery of media services in 5g networks,” IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 561– 574, 2018.
- L. Skorin-Kapov, M. Varela, T. Hoßfeld, and K.-T. Chen, “A survey of emerging concepts and challenges for qoe management of multimedia services,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 14, no. 2s, pp. 1–29, 2018.
- K. Khan and W. Goodridge, “Qoe in dash,” International Journal of Advanced Networking and Applications, vol. 9, no. 4, pp. 3515–3522, 2018.
- M. T. A. Abdullah, J. Lloret, A. Canovas´ Solbes, and L. Garc´ıa-Garc´ıa, “Survey of transportation of adaptive multimedia streaming service in internet,” Network Protocols and Algorithms, vol. 9, no. 1-2, pp. 85–125, 2017.
- A. Ahmed, Z. Shafiq, H. Bedi, and A. Khakpour, “Suffering from buffering? detecting qoe impairments in live video streams,” in 2017 IEEE 25th International Conference on Network Protocols (ICNP). IEEE, 2017, pp. 1–10.
- Staelens, Nicolas, Jonas De Meulenaere, Maxim Claeys, Glenn Van Wallendael, Wendy Van den Broeck, Jan De Cock, Rik Van de Walle, Piet Demeester, and Filip De Turck. "Subjective quality assessment of longer duration video sequences delivered over HTTP adaptive streaming to tablet devices." IEEE Transactions on Broadcasting 60, no. 4 (2014): 707-714.
- J. Chen, Z. Wei, S. Li, and B. Cao, “Artificial intelligence aided joint bit rate selection and radio resource allocation for adaptive video streaming over f-rans,” IEEE Wireless Communications, vol. 27, no. 2, pp. 36–43, 2020.
- O. El Marai, T. Taleb, M. Menacer, and M. Koudil, “On improving video streaming efficiency, fairness, stability, and convergence time through client–server cooperation,” IEEE Transactions on Broadcasting, vol. 64, no. 1, pp. 11–25, 2017.
- C. Zhou, C.-W. Lin, X. Zhang, and Z. Guo, “Tfdash: A fairness, stability, and efficiency aware rate control approach for multiple clients over dash,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 1, pp. 198–211, 2017.
- D. Wang, Y. Peng, X. Ma, W. Ding, H. Jiang, F. Chen, and J. Liu, “Adap-tive wireless video streaming based on edge computing: Opportunities and approaches,” IEEE Transactions on services Computing, vol. 12, no. 5, pp. 685–697, 2018.
- A. Bentaleb, B. Taani, A. C. Begen, C. Timmerer, and R. Zimmermann, “A survey on bitrate adaptation schemes for streaming media over http,” IEEE Communications Surveys & Tutorials, vol. 21, no. 1, pp. 562–585, 2018.
- C. B. Ameur, E. Mory, and B. Cousin, “Combining traffic-shaping methods with congestion control variants for http adaptive streaming,” Multimedia Systems, vol. 24, no. 1, pp. 1–18, 2018.
- D.-M. Chiu and R. Jain, “Analysis of the increase and decrease al-gorithms for congestion avoidance in computer networks,” Computer Networks and ISDN systems, vol. 17, no. 1, pp. 1–14, 1989.
- H. Mao, R. Netravali, and M. Alizadeh, “Neural adaptive video stream-ing with pensieve,” in Proceedings of the Conference of the ACM Special Interest Group on Data Communication, 2017, pp.197–210.
Abstract Views: 229
PDF Views: 1