Akhshabi S, Narayanaswamy S, Begen AC, Dovrolis C (2012) An experimental evaluation of rate-adaptive video players over HTTP. Signal process. Image Commun 27(4):271–287. https://doi.org/10.1016/j.image.2011.10.003
Android Developers webpage, ExoPlayer. Available online at: https://developer.android.com/guide/topics/media/exoplayer.html . Accessed: Jun. (2019)
Bampis CG, Li Z, Bovik AC (2018) SpatioTemporal feature integration and model fusion for full reference video quality assessment. IEEE Trans on Circuits and Syst for Video Tech 29:2256–2270. https://doi.org/10.1109/TCSVT.2018.2868262
[+]
Akhshabi S, Narayanaswamy S, Begen AC, Dovrolis C (2012) An experimental evaluation of rate-adaptive video players over HTTP. Signal process. Image Commun 27(4):271–287. https://doi.org/10.1016/j.image.2011.10.003
Android Developers webpage, ExoPlayer. Available online at: https://developer.android.com/guide/topics/media/exoplayer.html . Accessed: Jun. (2019)
Bampis CG, Li Z, Bovik AC (2018) SpatioTemporal feature integration and model fusion for full reference video quality assessment. IEEE Trans on Circuits and Syst for Video Tech 29:2256–2270. https://doi.org/10.1109/TCSVT.2018.2868262
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
Belda R (2013) Algoritmo de adaptación DASH: Look Ahead. Master Thesis. Universitat Politècnica de València. http://hdl.handle.net/10251/33359 .
Belda R, de Fez I, Arce P, Guerri J C (2018) Look ahead: a DASH adaptation algorithm. Proc. of the IEEE Int. Symp. On broadband multimed. Syst. And broadcast., Valencia, Spain: article no. 158. https://doi.org/10.1109/BMSB.2018.8436718 .
Blender Foundation webpage. Available online at: https://www.blender.org/foundation . Accessed: Jun. (2019).
Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20-3:273–297. https://doi.org/10.1023/A:1022627411411
DASH Industry forum webpage. Available online at: http://dashif.org . Accessed: Jun. (2019)
Ghadiyaram D, Pan J, Bovik AC (2019) A subjective and objective study of stalling events in mobile streaming videos. IEEE Trans on Circuits and Syst for Video Technol 29(1):183–197. https://doi.org/10.1109/TCSVT.2017.2768542
Ghent University. 4G/LTE bandwidth logs. Available online at: http://users.ugent.be/~jvdrhoof/dataset-4g . Accessed: Jun. (2019).
Github webpage. A DASH segment size aware rate adaptation model for DASH. Available online at: https://github.com/pari685/AStream . Accessed: Jun. (2019)
GitHub website. Dashgen, Multimedia Communications Group. Available online at: https://github.com/comm-iteam/dashgen . Accessed: Jun. (2019).
van der Hooft J, Petrangeli S, Wauters T, Huysegems R, Alface PR, Bostoen T, De Turck F (2016) HTTP/2-based adaptive streaming of HEVC video over 4G/LTE networks. IEEE Commun Lett 20(1):2177–2180. https://doi.org/10.1109/LCOMM.2016.2601087
Huang TY, Johari R, McKeown N, Trunnell M, Watson M (2014) A buffer-based approach to rate adaptation: evidence from a large video streaming service. Proc. of the 2014 ACM Conf. On SIGCOMM, Chicago, IL, USA: 187-198. https://doi.org/10.1145/2619239.2626296
Institute of Telecommunications and Multimedia Applications website. Look Ahead Demo. Available online at: https://lookahead.iteam.upv.es . Accessed: Jun. (2019)
ISO/IEC 23009–1:2014 (2014) Dynamic adaptive streaming over HTTP (DASH) - Part 1: media presentation description and segment formats.
Juluri P, Tamarapalli V, Medhi D (2015) SARA: segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP. Proc. of the IEEE Int. Conf. On Commun. Workshop (ICCW), London, UK: 1765-1770. https://doi.org/10.1109/ICCW.2015.7247436 .
Juluri P, Tamarapalli V, Medhi D (2016) QoE management in DASH systems using the segment aware rate adaptation algorithm. Proc. of the IEEE/IFIP Netw. Oper. And Manag. Symp. (NOMS), Istanbul, Turkey: 129-136. https://doi.org/10.1109/NOMS.2016.7502805 .
Kua J, Armitage G, Branch P (2017) A survey of rate adaptation techniques for dynamic adaptive streaming over HTTP. IEEE Commun Surv & Tutor 19(3):1842–1866. https://doi.org/10.1109/COMST.2017.2685630
Lee S, Youn K, Chung K (2015) Adaptive video quality control scheme to improve QoE of MPEG DASH. Proc. of IEEE Int. Conf. On Consum. Electron. (ICCE), Las Vegas, NV, USA: 126-127. https://doi.org/10.1109/ICCE.2015.7066348 .
Li S, Zhang F, Ma L, Ngan K (2011) Image quality assessment by separately evaluating detail losses and additive impairments. IEEE Trans. on Multimed. 13-5:935–949. https://doi.org/10.1109/TMM.2011.2152382
Liu C, Bouazizi I, Gabbouj M (2011) Rate adaptation for adaptive HTTP streaming. Proc. of the second annual ACM Conf. On multimed. Syst. (MMSys), San Jose, CA, USA: 169-174. https://doi.org/10.1145/1943552.1943575 .
Medium webpage (2016) Toward a practical perceptual video quality metric. Available online at: https://medium.com/netflix-techblog/toward-a-practical-perceptual-video-quality-metric-653f208b9652 . Accessed: Jun. 2019.
Mobile Video Service Performance Study (2015) HUAWEI white paper. Available online at: http://www.ctiforum.com/uploadfile/2015/0701/20150701091255294.pdf .
Mok RKP, Luo X, Chan EWW, Chang RKC (2012) QDASH: a QoE-aware DASH system. Proc. of multim. Syst. Conf. (MMSys), Chapel Hill, NC, USA: 11-22. https://doi.org/10.1145/2155555.2155558
Moldovan C, Hagn K, Sieber C, Kellerer W, Hoßfeld T (2017) Keep calm and don’t switch: about the relationship between switches and quality in HAS. Proc. of the Int. Teletraffic Congr. (ITC), Genoa, Italy: pp. 1-6. https://doi.org/10.23919/ITC.2017.8065802
Müller C, Lederer S, Timmerer C (2012) An evaluation of dynamic adaptive streaming over HTTP in vehicular environments. Proc. of the 4th workshop on mob. Video (MoVid), Chapel Hill, NC, USA: 37-42. https://doi.org/10.1145/2151677.2151686
Nguyen T, Vu T, Nguyen DV, Ngoc NP, and Thang TC (2015) QoE optimization for adaptive streaming with multiple VBR videos. Proc. of the Int. Conf. On comp., Manag. And Telecommun. (ComManTel), DaNang, Vietnam: 189-193. https://doi.org/10.1109/ComManTel.2015.7394285 .
Qin Y, H. Shuai, Pattipati K R, Qian F, Sen S, Wang B, Yue C (2018) ABR Streaming of VBR-encoded videos: characterization, challenges, and solutions. Proc. of ACM CoNext 2018, Heraklion, Greece: 366–378. https://doi.org/10.1145/3281411.3281439 .
Samain J, Carofiglio G, Muscariello L, Papalini M, Sardara M, Tortelli M, Rossi D (2017) Dynamic adaptive video streaming: towards a systematic comparison of ICN and TCP/IP. IEEE Trans on Multimed 19(10):2166–2181. https://doi.org/10.1109/TMM.2017.2733340
Sheikh H, Bovik A (2006) Image information and visual quality. IEEE Trans on Image Process 15(2):430–444. https://doi.org/10.1109/TIP.2005.859378
Shuai Y, Herfet T (2016). A buffer dynamic stabilizer for low-latency adaptive video streaming. Proc. of the Int. Conf. on Consum. Electron., Berlin: 1–5. https://doi.org/10.1109/ICCE-Berlin.2016.7684742 .
Tavakoli S, Egger S, Seufert M, Schatz R, Brunnström K, García N (2016) Perceptual quality of HTTP adaptive streaming strategies: cross-experimental analysis of multi-laboratory and crowdsourced subjective studies. IEEE Journal on Select Areas in Commun 34-8:2141–2153. https://doi.org/10.1109/JSAC.2016.2577361
Yarnagula H K, Juluri P, Mehr S K, Tamarapalli V, Medhi D (2019) QoE for Mobile clients with segment-aware rate adaptation algorithm (SARA) for DASH video streaming. ACM trans. On multimed. Comput., Commun., and Appl. (TOMM) 15(2):article no. 36 https://doi.org/10.1145/3311749 .
Yin X, Sekar V, Sinopoli B (2014) Toward a principled framework to design dynamic adaptive streaming algorithms over HTTP. Proc. of the 13th ACM workshop on hot topics in Netw. (HotNets), Los Angeles, CA, USA: 1-7. https://doi.org/10.1145/2670518.2673877 .
YouTube webpage (2019) Youtube press. Available online at: https://www.youtube.com/yt/about/press . Accessed: Jun. 2019.
Youtube webpage, Google I/O ‘18: Building feature-rich media apps with ExoPlayer. Available online at: https://youtu.be/svdq1BWl4r8?t=2m . Published: May (2018)
Yu L, Tillo T, Xiao J (2017) QoE-driven dynamic adaptive video streaming strategy with future information. IEEE Trans on Broadcast 63-3:523–534. https://doi.org/10.1109/TBC.2017.2687698
Zhao S, Li Z, Medhi D, Lai P, Liu S (2017) Study of user QoE improvement for dynamic adaptive streaming over HTTP (MPEG-DASH). Proc. of the Int. Conf. On Comput., network. And Commun. (ICNC): multimed. Comput. And Commun., Santa Clara, CA, USA: 566-570. https://doi.org/10.1109/ICCNC.2017.7876191 .
Zhou Y, Duan Y, Sun J, Guo Z (2014) Towards a simple and smooth rate adaption for VBR video in DASH. Proc. of the IEEE Vis. Commun. and Image Process. Conf, Valletta, pp 9–12. https://doi.org/10.1109/VCIP.2014.7051491
Zhou C, Lin C-W, Guo Z (2016) mDASH: a Markov decision-based rate adaptation approach for dynamic HTTP streaming. IEEE Trans. on Multimed 18(4):738–751. https://doi.org/10.1109/TMM.2016.2522650
[-]