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An automated model for the assessment of QoE of adaptive video streaming over wireless networks

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An automated model for the assessment of QoE of adaptive video streaming over wireless networks

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Taha, M.; Ali, A.; Lloret, J.; Gondim, PRL.; Canovas, A. (2021). An automated model for the assessment of QoE of adaptive video streaming over wireless networks. Multimedia Tools and Applications. 80(17):26833-26854. https://doi.org/10.1007/s11042-021-10934-9

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/196897

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Title: An automated model for the assessment of QoE of adaptive video streaming over wireless networks
Author: Taha, Miran Ali, Aree Lloret, Jaime Gondim, Paulo R. L. Canovas, Alejandro
UPV Unit: Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia
Issued date:
Abstract:
[EN] Nowadays, heterogeneous devices are widely utilizing Hypertext Transfer Protocol (HTTP) to transfer the data. Furthermore, HTTP adaptive video streaming (HAS) technology transmits the video data over wired and wireless ...[+]
Subjects: HTTP adaptive streaming , Correlation coefficient , QoE , QoS , Subjective methodology
Copyrigths: Reserva de todos los derechos
Source:
Multimedia Tools and Applications. (issn: 1380-7501 )
DOI: 10.1007/s11042-021-10934-9
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/s11042-021-10934-9
Project ID:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-84802-C2-1-P/ES/RED COGNITIVA DEFINIDA POR SOFTWARE PARA OPTIMIZAR Y SECURIZAR TRAFICO DE INTERNET DE LAS COSAS CON INFORMACION CRITICA/
Thanks:
This work has been partially supported by the "Ministerio de Economia y Competitividad" in the "Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia, Subprograma Estatal de Generacion de ...[+]
Type: Artículo

References

Abar T, Letaifa AB, Elasmi S (2018) Enhancing QoE based on machine learning and DASH in SDN networks. 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), IEEE, Krakow, Poland, pp. 258–263, https://doi.org/10.1109/WAINA.2018.00095

Absolute Category Rating (ACR) ITU-R BT.500–12. Recommendation ITU-R BT.500-13Methodology for the subjective assessment of the quality of television pictures (Jan. 2012), [Accessed November 2019 Online]

Barman N, Martini MG (2019) QoE modeling for HTTP adaptive video streaming–a survey and open challenges. IEEE Access 7:30831–30859. https://doi.org/10.1109/ACCESS.2019.2901778 [+]
Abar T, Letaifa AB, Elasmi S (2018) Enhancing QoE based on machine learning and DASH in SDN networks. 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), IEEE, Krakow, Poland, pp. 258–263, https://doi.org/10.1109/WAINA.2018.00095

Absolute Category Rating (ACR) ITU-R BT.500–12. Recommendation ITU-R BT.500-13Methodology for the subjective assessment of the quality of television pictures (Jan. 2012), [Accessed November 2019 Online]

Barman N, Martini MG (2019) QoE modeling for HTTP adaptive video streaming–a survey and open challenges. IEEE Access 7:30831–30859. https://doi.org/10.1109/ACCESS.2019.2901778

Barman N, Zadtootaghaj S, Schmidt S, Martini MG, Möller S (2018) An objective and subjective quality assessment study of passive gaming video streaming. International Journal of Network Management, pp. e2054. DOI: https://doi.org/10.1002/nem.2054

Barman N, Jammeh E, Ghorashi SA, Martini MG (2019) No-reference video quality estimation based on machine learning for passive gaming video streaming applications. IEEE Access 7:74511–74527. https://doi.org/10.1109/ACCESS.2019.2920477

Bulkan U, Dagiuklas T (2019) Predicting quality of experience for online video service provisioning. Multimed Tools Appl 78(13):18787–18811. https://doi.org/10.1007/s11042-019-7164-9

Chen Y, Wu K, Zhang Q (2014) From QoS to QoE: a tutorial on video quality assessment. IEEE Commun Surveys Tutorials 17(2):1126–1165. https://doi.org/10.1109/COMST.2014.2363139

Chikkerur S, Sundaram V, Reisslein M, Karam LJ (2011) Objective video quality assessment methods: a classification, review, and performance comparison. IEEE Trans Broadcast 57(2):165–182. https://doi.org/10.1109/TBC.2011.2104671

Cisco report, [Accessed November 2019 Online]: http://bit.ly/2gg1F6B

Claeys M, Latre S, Famaey J, De Turck F (2014) Design and evaluation of a self-learning HTTP adaptive video streaming client. IEEE Commun Lett 18(4):716–719. https://doi.org/10.1109/LCOMM.2014.020414.132649

Cofano G, De Cicco L, Zinner T, Nguyen-Ngoc A, Tran-Gia P, Mascolo S (2016) Design and experimental evaluation of network-assisted strategies for HTTP adaptive streaming. In Proceedings of the 7th International Conference on Multimedia Systems, pp. 1–12. https://doi.org/10.1145/2910017.2910597

Duanmu Z, Zeng K, Ma K, Rehman A, Wang Z (2016) A quality-of-experience index for streaming video. IEEE J Selected Topics Sign Process 11(1):154–166. https://doi.org/10.1109/10.1109/JSTSP.2016.2608329

García L, Lloret J, Turro C, Taha M (2016) QoE assesment of MPEG-DASH in polimedia e-learning system. International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, pp. 1117–1123. DOI: https://doi.org/10.1109/ICACCI.2016.7732194

García B, López-Fernández L, Gortázar F, Gallego M (2019) Practical Evaluation of VMAF Perceptual Video Quality for WebRTC Aepplications. Journal of Electronics, vol. 9, no. 2. https://doi.org/10.3390/electronics8080854

Guan-MingSu XS, Bai Y, Wang M, Vasilakos AV, Wang H (2016) QoE in video streaming over wireless networks: perspectives and research challenges. Wirel Netw 22(5):1571–1593. https://doi.org/10.1007/s11276-015-1028-7

Gutterman C, Guo K, Arora S, Wang X, Wu L, Katz-Bassett E, Zussman G (2019) Requet: Real-time QoE detection for encrypted YouTube traffic. In Proceedings of the 10th ACM Multimedia Systems Conference, pp. 48–59. https://doi.org/10.1145/3304109.3306226

Huawei report, [Accessed December 2019 Online]: https://www.huawei.com/minisite/hwmbbf15/img/video_coverage_whitepaper_en.pdf.

ITU-T Rec. P.1203. (2017) Parametric bitstream-based quality assessment of progressive download and adaptive audiovisual streaming services over reliable transport. ITU-T Rec. P.1203

Juluri P, Tamarapalli V, Medhi D (2015) Measurement of quality of experience of video-on-demand services: a survey. IEEE Commun Surveys Tutorials 18(1):401–418. https://doi.org/10.1109/COMST.2015.2401424

Juluri P, Tamarapalli V, Medhi D (2016) Measurement of quality of experience of video-on-demand services: a survey. IEEE Commun Surveys Tutorials 18(1):401–418. https://doi.org/10.1109/COMST.2015.2401424

Liu X, Nan Z, Richard Yu F, Chen Y, Tang J, Leung VCM (2018) Cooperative video transmission strategies via caching in small-cell networks. IEEE Trans Veh Technol 67(12):12204–12217. https://doi.org/10.1109/TVT.2018.2874258

MingfuLi C-LY, Shao-Yu L (2018) Real-time QoE monitoring system for video streaming services with adaptive media playout. Int J Digital Multimed Broadcast 2018:1–11. https://doi.org/10.1155/2018/2619438

Mok R, Luo X, Chan E, Chang R (2012) QDASH: A QoE-aware DASH system. Proceedings of the 3rd Multimedia Systems Conference, pp. 11–22. https://doi.org/10.1145/2155555.2155558

Moorthy AK, Seshadrinathan K, Soundararajan R, Bovik AC (2010) Wireless video quality assessment: a study of subjective scores and objective algorithms. IEEE trans Circuits Syst Vid Technol 20(4):587–599. https://doi.org/10.1109/TCSVT.2010.2041829

Nam H, Kim K-H, Schulzrinne H (2016) QoE matters more than QoS: Why people stop watching cat videos. In IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, IEEE, pp. 1–9. https://doi.org/10.1109/INFOCOM.2016.7524426

Nunome T, Mizutani K (2019) The joint effect of wireless LAN reliable groupcast and a rate-adaptation mechanism on QoE of audio and video transmission. in Proc. IEEE 26th International Conference on Telecommunications (ICT), IEEE, pp. 149–153. https://doi.org/10.1109/ICT.2019.8798643

Nunome T, Tani H (2017) The effect of seeking operation on QoE of HTTP adaptive streaming services. Int J Comput Netw Commun (IJCNC) 9(2):1–18. https://doi.org/10.5121/ijcnc.2017.9201

Orsolic I, Pevec D, Suznjevic M, Skorin-Kapov L (2017) A machine learning approach to classifying YouTube QoE based on encrypted network traffics. Multimed Tools Appl 76(21):22267–22301. https://doi.org/10.1007/s11042-017-4728-4

Pal D, Vanijja V (2017) Effect of network QoS on user QoE for a mobile video streaming service using H. 265/VP9 codec. Proced Comput Sci 111:214–222. https://doi.org/10.1016/j.procs.2017.06.056

Petrangeli S, Van Der Hooft J, Wauters T, De Turck F (2018) Quality of experience-centric management of adaptive video streaming services: status and challenges. ACM Trans Multimed Comput Commun Appl (TOMM) 14(2):1–29. https://doi.org/10.1145/3165266

Poojary S, El-Azouzi R, Altman E, Sunny A, Triki I, Haddad M, Jimenez T, Valentin S, Tsilimantos D (2018) Analysis of QoE for adaptive video streaming over wireless networks. 16th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), IEEE, pp. 1–8, https://doi.org/10.23919/WIOPT.2018.8362846

Retal S, Bagaa M, Taleb T, Flinck H (2017) Content delivery network slicing: QoE and cost awareness. IEEE International Conference on Communications (ICC), IEEE, pp. 1–6, https://doi.org/10.1109/ICC.2017.7996499

Rodrigues F, Sousa I, Queluz MP, Rodrigues A (2018) QoE-aware scheduling algorithm for adaptive HTTP video delivery in wireless networks. Wireless Communications and Mobile computing, vol. 2018. DIO: https://doi.org/10.1155/2018/9736360

Schatz R, Sackl A, Timmerer C, Gardlo B (2017) Towards subjective quality of experience assessment for omnidirectional video streaming." Ninth International Conference on Quality of Multimedia Experience (QoMEX), IEEE, no. 6, pp. 1-, https://doi.org/10.1109/QoMEX.2017.7965657

Seufert M, Egger S, Slanina M, Zinner T, Hoßfeld T, Tran-Gia P (2014) A survey on quality of experience of HTTP adaptive streaming. IEEE Commun Surveys Tutorials 17(1):469–492. https://doi.org/10.1109/COMST.2014.2360940

Singh S, Andrews JG, de Veciana G (2012) Interference shaping for improved quality of experience for real-time video streaming. IEEE J Selected Areas Commun 30(7):1259–1269. https://doi.org/10.1109/JSAC.2012.120811

Stensen JMG (2012) Evaluating QoS and QoE Dimensions in Adaptive Video Streaming. Master's thesis, Institutt for telematikk, https://doi.org/10.12142/ZTECOM.201901004

Streijl RC, Winkler S, Hands DS (2016) Mean opinion score (MOS) revisited: methods and applications, limitations and alternatives. Multimedia Systems 22(2):213–227. https://doi.org/10.1007/s00530-014-0446-1

Taha M (2016) A novel CDN testbed for fast deploying HTTP adaptive video streaming. Proceedings of the 9th EAI International Conference on Mobile Multimedia Communications, pp. 65–71. DOI: https://doi.org/10.4108/eai.18-6-2016.2264163

Taha M, Lloret J, Ali A, Garcia L (2018) Adaptive video streaming testbed design for performance study and assessment of QoE. Int J Commun Syst 31(9):e3551. https://doi.org/10.1002/dac.3551

Thang TC, Le HT, Nguyen HX, Pham AT, Kang JW, Ro YM (2013) Adaptive video streaming over HTTP with dynamic resource estimation. J Commun Netw 15(6):635–644. https://doi.org/10.1109/JCN.2013.000112

Timmerer C, Zabrovskiy A (2019) Automating QoS and QoE Evaluation of HTTP Adaptive Streaming Systems. ZTE COMMUNICATIONS, vol. 17, no. 1

Trakas P, Adelantado F, Zorba N, Verikoukis C (2017) A quality of experience-aware association algorithm for 5G heterogeneous networks. In 2017 IEEE International Conference on Communications (ICC), IEEE, pp. 1–6. DOI: https://doi.org/10.1109/ICC.2017.7996869

Villa BJ, Heegaard PE (2012) Improving Fairness in QoS and QoE domains for Adaptive Video Streaming. International Journal on Advances in Networks and Services vol. 5, no. 3, pp. 4

Qingyong Wang, Hong-Ning Dai, Di Wu, and Hong Xiao (2018) Data analysis on video streaming QoE over mobile networks. Eurasip J Wireless Commun Netw, no. 1, pp.173, https://doi.org/10.1186/s13638-018-1180-8

Wenjing L, Yu P, Wang R, Lei F, Dong O, Xuesong Q (2017) Quality of experience evaluation of HTTP video streaming based on user interactive behaviors. J China Univ Posts Telecommun 24(3):24–32. https://doi.org/10.1016/S1005-8885(17)60208-5

Xu Y, Zhou Y, Chiu D-M (2014) Analytical QoE models for bit-rate switching in dynamic adaptive streaming systems. IEEE Trans Mob Comput 13(12):2734–2748. https://doi.org/10.1109/TMC.2014.2307323

Zeng H, Fang Y (2013) Implementation of video transcoding client based on FFMPEG. In Advanced Materials Research, vol. 756, Trans Tech Publications Ltd, pp. 1748–1752. 10.4028/www.scientific.net/AMR.756-759.1748

Zhang W, Wen Y, Chen Z, Khisti A (2013) QoE-driven cache management for HTTP adaptive bit rate streaming over wireless networks. IEEE Trans Multimed 15(6):1431–1445. https://doi.org/10.1109/TMM.2013.2247583

Zhao T, Liu Q, Chen CW (2016) QoE in video transmission: a user experience-driven strategy. IEEE Commun Surveys Tutorials 19(1):285–302. https://doi.org/10.1109/COMST.2016.2619982

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