| dc.identifier.citation | [1] K. Brunnstr¨om et al., “Definitions of Quality of Experience,” Qualinet White Paper, 2013. [2] International Telecommunication Union, “Vocabulary for Performance, Quality of Service and Quality of Experience,” 2017, recommendation P.10/G.100. [3] 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 and Tutorials, vol. 21, no. 1, pp. 562–585, 2019. [4] Conviva, “Conviva’s State of Streaming Q2 2022,” September 2022, Report, https://www.conviva.com/wp-content/uploads/2022/09/Q2-SoS. pdf. [5] Sandvine, “The Global Internet Phenomena Report January 2023,” January 2023, Report, https://www.sandvine.com/ global-internet-phenomena-report-2023. [6] A. Seufert, F. Wamser, D. Yarish, H. Macdonald, and T. Hoßfeld, “QoE Models in the Wild: Comparing Video QoE Models Using a Crowdsourced Data Set,” in QoMEX 2021. [7] F. Chen, C. Zhang, F. Wang, and J. Liu, “Crowdsourced Live Streaming Over the Cloud,” in INFOCOM 2015. [8] U. Reiter et al., “Factors Influencing Quality of Experience,” in Quality of Experience: Advanced Concepts, Applications and Methods. Springer, 2014. [9] 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, vol. 14, no. 2s, p. 1–29, 2018. [10] T. Zhao, Q. Liu, and C. W. Chen, “QoE in Video Transmission: A User Experience-Driven Strategy,” IEEE Communications Surveys & Tutorials, vol. 19, no. 1, pp. 285–302, 2017. [11] P. Juluri, V. Tamarapalli, and D. Medhi, “Measurement of Quality of Experience of Video-on-Demand Services: A Survey,” IEEE Communications Surveys & Tutorials, vol. 18, no. 1, pp. 401–418, 2016. [12] N. Barman and M. G. Martini, “QoE Modeling for HTTP Adaptive Video Streaming – A Survey and Open Challenges,” IEEE Access, vol. 7, pp. 30 831–30 859, 2019. [13] A. A. Barakabitze, N. Barman, A. Ahmad, S. Zadtootaghaj, L. Sun, M. G. Martini, and L. Atzori, “QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey,” IEEE Communications Surveys & Tutorials, vol. 22, no. 1, pp. 526–565, 2020. [14] P. Davis, C. D. Creusere, and J. Kroger, “EEG and the Human Perception of Video Quality: Impact of Channel Selection on Discrimination,” in GlobalSIP 2013. [15] Q. Huynh-Thu and M. Ghanbari, “Scope of Validity of PSNR in Image/Video Quality Assessment,” Electronics Letters, vol. 44, no. 13, p. 800–801, 2008. [16] Z. Li, A. Aaron, I. Katsavounidis, A. Moorthy, and M. Manohara, “Toward A Practical Perceptual Video Quality Metric,” 2016, Netflix Technology Blog. https://medium.com/netflix-techblog/ toward-a-practical-perceptual-video-quality-metric-653f208b9652. [17] F. Tashtarian, A. Bentaleb, H. Amirpour, S. Gorinsky, J. Jiang, H. Hellwagner, and C. Timmerer, “ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming,” in NSDI 2024. [18] L. Peroni, S. Gorinsky, F. Tashtarian, and C. Timmerer, “Empowerment of Atypical Viewers via Low-Effort Personalized Modeling of Video Streaming Quality,” in CoNEXT 2023. [19] X. Zhang, Y. Ou, S. Sen, and J. Jiang, “Sensei: Aligning Video Streaming Quality with Dynamic User Sensitivity,” in NSDI 2021. [20] X. Zuo, J. Yang, M. Wang, and Y. Cui, “Adaptive Bitrate with User- Level QoE Preference for Video Streaming,” in INFOCOM 2022. [21] J. Gozdecki, A. Jajszczyk, and R. Stankiewicz, “Quality of Service Terminology in IP Networks,” IEEE Communications Magazine, vol. 41, no. 3, pp. 153–159, 2003. [22] V. Nathan, V. Sivaraman, R. Addanki, M. Khani, P. Goyal, and M. Alizadeh, “End-to-End Transport for Video QoE Fairness,” in SIGCOMM 2019. [23] Z. Duanmu, A. Rehman, and Z. Wang, “A Quality-of-Experience Database for Adaptive Video Streaming,” IEEE Transactions on Broadcasting, vol. 64, no. 2, pp. 474–487, 2018. [24] Z. Duanmu, W. Liu, Z. Li, D. Chen, Z. Wang, Y. Wang, and W. Gao, “Assessing the Quality-of-Experience of Adaptive Bitrate Video Streaming,” arXiv, no. 2008.08804, 2020. [25] D. Z. Rodr´ıguez, R. L. Rosa, and G. Bressan, “Video Quality Assessment in Video Streaming Services Considering User Preference for Video Content,” in ICCE 2014. [26] D. Ghadiyaram, J. Pan, and A. C. Bovik, “A Subjective and Objective Study of Stalling Events in Mobile Streaming Videos,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 1, pp. 183–197, 2019. [27] International Telecommunication Union, “Methodologies for the Subjective Assessment of the Quality of Television Images,” 2023, recommendation BT.500-15. [28] ——, “Subjective Video Quality Assessment Methods for Multimedia Applications,” 2022, recommendation P.910. [29] H. Sheikh, M. Sabir, and A. Bovik, “A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms,” IEEE Transactions on Image Processing, vol. 15, no. 11, pp. 3440–3451, 2006. [30] N. Eswara, K. Manasa, A. Kommineni, S. Chakraborty, H. P. Sethuram, K. Kuchi, A. Kumar, and S. S. Channappayya, “A Continuous QoE Evaluation Framework for Video Streaming Over HTTP,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 11, pp. 3236–3250, 2018. [31] Q. Huynh-Thu, M.-N. Garcia, F. Speranza, P. Corriveau, and A. Raake, “Study of Rating Scales for Subjective Quality Assessment of High- Definition Video,” IEEE/ACM Transactions on Networking, vol. 57, no. 1, pp. 1–14, 2011. [32] T. Tominaga, T. Hayashi, J. Okamoto, and A. Takahashi, “Performance Comparisons of Subjective Quality Assessment Methods for Mobile Video,” in QoMEX 2010. [33] X. Yin, A. Jindal, V. Sekar, and B. Sinopoli, “A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP,” in SIGCOMM 2015. [34] K. Spiteri, R. Urgaonkar, and R. K. Sitaraman, “BOLA: Near-Optimal Bitrate Adaptation for Online Videos,” in INFOCOM 2016. [35] I. de Fez, R. Belda, and J. C. Guerri, “New Objective QoE Models for Evaluating ABR Algorithms in DASH,” Computer Communications, vol. 158, pp. 126–140, 2020. [36] F. Y. Yan, H. Ayers, C. Zhu, S. Fouladi, J. Hong, K. Zhang, P. Levis, and K. Winstein, “Learning in Situ: A Randomized Experiment in Video Streaming,” in NSDI 2020. [37] T. Huang, C. Zhou, X. Yao, R. X. Zhang, C. Wu, B. Yu, and L. Sun, “Quality-Aware Neural Adaptive Video Streaming with Lifelong Imitation Learning,” IEEE Journal on Selected Areas in Communications, vol. 38, no. 10, pp. 2324–2342, 2020. [38] A. Bentaleb, A. C. Begen, and R. Zimmermann, “SDNDASH: Improving QoE of HTTP Adaptive Streaming Using Software Defined Networking,” in MM 2016. [39] 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. [40] C. G. Bampis and A. C. Bovik, “Learning to Predict Streaming Video QoE: Distortions, Rebuffering and Memory,” arXiv, no. 1703.00633, 2017. [41] A. Raake, M.-N. Garcia, W. Robitza, P. List, S. G¨oring, and B. Feiten, “A Bitstream-Based, Scalable Video-Quality Model for HTTP Adaptive Streaming: ITU-T P.1203.1,” in QoMEX 2017. [42] H. T. T. Tran, D. V. Nguyen, N. P. Ngoc, and T. C. Thang, “Overall Quality Prediction for HTTP Adaptive Streaming Using LSTM Network,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 8, pp. 3212–3226, 2021. [43] H. Mao, R. Netravali, and M. Alizadeh, “Neural Adaptive Video Streaming with Pensieve,” in SIGCOMM 2017. [44] T. Y. Huang, R. Johari, N. McKeown, M. Trunnell, and M. Watson, “A Buffer-Based Approach to Rate Adaptation: Evidence From a Large Video Streaming Service,” in SIGCOMM 2014. [45] K. Spiteri, R. K. Sitaraman, and D. Sparacio, “From Theory to Practice: Improving Bitrate Adaptation in the DASH Reference Player,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 15, no. 2s, p. 1–29, 2019. [46] Z. Duanmu, W. Liu, Z. Li, D. Chen, Z. Wang, Y. Wang, and W. Gao, “The Waterloo Streaming Quality-of-Experience Database-IV,” IEEE Dataport, 2020, https://dx.doi.org/10.21227/j15a-8r35. [47] L. Peroni, S. Gorinsky, F. Tashtarian, and C. Timmerer, “iQoE Dataset and Code,” GitHub, 2023, https://github.com/Leo-rojo/iQoE Dataset and Code. [48] H. Mao et al., “Park: An Open Platform for Learning-Augmented Computer Systems,” in NeurIPS 2019. [49] E. Rosch, “Principles of Categorization,” in Cognition and Categorization. Lawrence Erlbaum, 1978. [50] A. K. Moorthy, L. K. Choi, A. C. Bovik, and G. de Veciana, “Video Quality Assessment on Mobile Devices: Subjective, Behavioral and Objective Studies,” IEEE Journal of Selected Topics in Signal Processing, vol. 6, no. 6, pp. 652–671, 2012. [51] C. Chen, L. K. Choi, G. de Veciana, C. Caramanis, R. W. Heath, and A. C. Bovik, “Modeling the Time – Varying Subjective Quality of HTTP Video Streams With Rate Adaptations,” IEEE Transactions on Image Processing, vol. 23, no. 5, pp. 2206–2221, 2014. [52] Z. Duanmu, K. Zeng, K. Ma, A. Rehman, and Z. Wang, “A Qualityof- Experience Index for Streaming Video,” IEEE Journal of Selected Topics in Signal Processing, vol. 11, no. 1, pp. 154–166, 2017. [53] J. Y. Lin, L. Jin, S. Hu, I. Katsavounidis, Z. Li, A. Aaron, and C.- C. J. Kuo, “Experimental Design and Analysis of JND Test on Coded Image/Video,” SPIE Applications of Digital Image Processing XXXVIII, vol. 9599, pp. 324–334, 2015. [54] M. Claeys, S. Latr´e, J. Famaey, T. Wu, W. Van Leekwijck, and F. D. Turck, “Design and Optimisation of a (FA)Q-Learning-Based HTTP Adaptive Streaming Client,” Connection Science, vol. 26, no. 1, pp. 25–43, 2014. [55] S. Petrangeli, J. Famaey, M. Claeys, S. Latr´e, and F. De Turck, “QoEDriven Rate Adaptation Heuristic for Fair Adaptive Video Streaming,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 12, no. 2, pp. 1–24, 2015. [56] H. Berm´udez-Orozco, J.-M. Martinez-Caro, R. Sanchez-Iborra, J. Arciniegas, and M.-D. Cano, “Live Video-Streaming Evaluation Using the ITU-T P.1203 QoE Model in LTE Networks,” Computer Networks, vol. 165, 2019. [57] D. Nguyen, N. Pham Ngoc, and T. C. Thang, “QoE Models for Adaptive Streaming: A Comprehensive Evaluation,” Future Internet, vol. 14, no. 5, 2022. [58] Y. Liu, S. Dey, F. Ulupinar, M. Luby, and Y. Mao, “Deriving and Validating User Experience Model for DASH Video Streaming,” IEEE Transactions on Broadcasting, vol. 61, no. 4, pp. 651–665, 2015. [59] Z. Duanmu, W. Liu, D. Chen, Z. Li, , Z. Wang, Y. Wang, and W. Gao, “A Knowledge-Driven Quality-of-Experience Model for Adaptive Streaming Videos,” arXiv, no. 1911.07944, 2019. [60] A. V. Ivchenko, P. A. Kononyuk, A. V. Dvorkovich, and L. A. Antiufrieva, “Study on the Assessment of the Quality of Experience of Streaming Video,” in SYNCHROINFO 2020. [61] B. Taraghi, M. Nguyen, H. Amirpour, and C. Timmerer, “Intense: In- Depth Studies on Stall Events and Quality Switches and Their Impact on the Quality of Experience in HTTP Adaptive Streaming,” IEEE Access, vol. 9, pp. 118 087–118 098, 2021. [62] J. De Vriendt, D. De Vleeschauwer, and D. Robinson, “Model for Estimating QoE of Video Delivered Using HTTP Adaptive Streaming,” in IM 2013. [63] F. Gao and L. Han, “Implementing the Nelder-Mead Simplex Algorithm with Adaptive Parameters,” Computational Optimization and Applications, vol. 51, pp. 259–277, 2012. [64] Z. Duanmu, W. Liu, D. Chen, Z. Li, Z. Wang, Y. Wang, and W. Gao, “A Bayesian Quality-of-Experience Model for Adaptive Streaming Videos,” ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 18, no. 3s, pp. 1–24, 2023. [65] N. Eswara, S. Ashique, A. Panchbhai, S. Chakraborty, H. P. Sethuram, K. Kuchi, A. Kumar, and S. S. Channappayya, “Streaming Video QoE Modeling and Prediction: A Long Short-Term Memory Approach,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 3, pp. 661–673, 2020. [66] Y. Liu and J. Y. B. Lee, “A Unified Framework for Automatic Qualityof- Experience Optimization in Mobile Video Streaming,” in INFOCOM 2016. [67] C. Gutterman, B. Fridman, T. Gilliland, Y. Hu, and G. Zussman, “STALLION: Video Adaptation Algorithm for Low-Latency Video Streaming,” in MMsys 2020. [68] T. Huang, C. Zhou, R.-X. Zhang, C. Wu, X. Yao, and L. Sun, “Stick: A Harmonious Fusion of Buffer-Based and Learning-Based Approach for Adaptive Streaming,” in INFOCOM 2020. [69] B. Alt, T. Ballard, R. Steinmetz, H. Koeppl, and A. Rizk, “CBA: Contextual Quality Adaptation for Adaptive Bitrate Video Streaming,” in INFOCOM 2019. [70] Z. Akhtar, S. Rao, B. Ribeiro, Y. S. Nam, J. Chen, J. Zhan, R. Govindan, E. Katz-Bassett, and H. Zhang, “Oboe: Auto-Tuning Video ABR Algorithms to Network Conditions,” in SIGCOMM 2018. [71] C. Wang, A. Rizk, and M. Zink, “SQUAD: A Spectrum-Based Quality Adaptation for Dynamic Adaptive Streaming over HTTP,” in MMSys 2016. | es |
