Abstract
Adaptive streaming allows for dynamic adaptation of the bitrate to varying network conditions, to guarantee the best user experience. Adaptive bitrate algorithms face a significant challenge in correctly estimating the throughput, as the throughput varies widely over time. The current throughput estimation methods cannot distinguish between throughput fluctuations of different amplitude and frequency. In this paper, we propose a throughput estimation method that accurately estimates the throughput based on previous throughput samples. It is robust to short term and small fluctuations, and sensitive to large fluctuations in throughput. Furthermore, we propose a rate adaptive algorithm for video on demand (VoD) services that selects the quality of the video based on the estimated throughput and playback buffer occupancy. The objective of the rate adaptive algorithms is to guarantee high video quality to improve user experience. The proposed algorithm dynamically adjusts the quality level of the video stream. The proposed method selects high quality video segments, while minimizing the risk of playback interruption. Furthermore, the proposed method minimizes the frequency of video rate changes. We show that the algorithm smoothly switches the video rate to improve user experience. Furthermore, we determine that it efficiently utilizes network resources to achieve a high video rate; competing HTTP clients achieve equitable video rates. We also confirm that variations in the playback buffer size and segment duration do not affect the performance of the proposed algorithm.
Similar content being viewed by others
References
Dobrian, F., Awan, A., Joseph, D., Ganjam, A., Zhan, J., Sekar, V., Stoica, I., Zhang, H.: Understanding the impact of video quality on user engagement. ACM SIGCOM Comput. Commun. Review. 56(3), 91–99 (2013). https://doi.org/10.1145/2018436.2018478
Ni, P., Eg, R., Eichhorn, A., Griwodz, C., Halvorsen, P.: Flicker effects in adaptive video streaming to handheld devices. In: Proceedings of ACM Int. Conf. on Multimedia, pp. 463–472. Arizona, USA (2011). https://doi.org/10.1145/2072298.2072359
Liu, Y., Dey, S., Gillies, D., Ulupinar, F., Luby, M.: User experience modeling for DASH video. In: Proceedings of IEEE Packet Video Workshop, pp. 1–8. San Jose, USA, (2013). https://doi.org/10.1109/pv.2013.6691459
Shen, Y.., Yitong, L., Yang, H., Yang, D.: Quality of Experience study on dynamic adaptive streaming based on HTTP. IEICE Tran. Commun. 98(1), 62–70 (2015). https://doi.org/10.1587/transcom.e98.b.62
Egger, S., Gardlo, B., Seufert, M., Schatz, R.: The impact of adaptation strategies on perceived quality of http adaptive streaming. In: Proceedings of ACM Workshop Design, Quality and Deployment Adaptive Video Streaming, pp. 31–36. Sydney, Australia: (2014). https://doi.org/10.1145/2676652.2676658
Dubin, R., Hadar, O., Dvir, A.: The effect of client buffer and MBR consideration on DASH adaptation logic. In: Proceedings of IEEE Wireless Commun. and Networking Conference, pp. 2178–2183. Shanghai, China: (2013). https://doi.org/10.1109/wcnc.2013.6554900
Rahman, W., Chung, K.: Buffer-based adaptive bitrate algorithm for streaming over HTTP. KSII Tran. Internet and Inform. Syst. 9(11), 4585–4622 (2015). https://doi.org/10.3837/tiis.2015.11.019
VideoLAN. (2013). Vlc sourece code. [Online]. Available: http://www.videolan.org/ vlc/download-sources.html
Akhshabi, S., Begen, A.C., Dovrolis, C.: An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP. In: Proceedings of ACM Conf. on Multimedia System, pp. 157–168. California, USA: (2011). https://doi.org/10.1145/1943552.1943574
Thang, T.C., Ho, Q.D., Kang, J.W., Pham, A.T.: Adaptive streaming of audiovisual content using MPEG DASH. IEEE Trans. Consumer Electron. 58(1), 78–85 (2012). https://doi.org/10.1109/tce.2012.6170058
Liu, C., Bouazizi, I., Gabbouj, M.: Rate adaptation for adaptive HTTP streaming. In: Proceedings of ACM Conf. on Multimedia Syst., pp. 169–174. California, USA: (2011). https://doi.org/10.1145/1943552.1943575
Miller, K., Quacchio, E., Gennari, G., Wolisz, A.: Adaptation algorithm for adaptive streaming over HTTP. In: Proceeding of IEEE Packet Video Workshop, pp. 173–178. Munich, Germany: (2012). https://doi.org/10.1109/pv.2012.6229732
Juluri, P., Tamarapalli, V., Medhi, D.: SARA: Segment aware rate adaptation algorithm for dynamic adaptive streaming over HTTP. In: Proceedings of IEEE Int. Conf. on Commun. Workshop, pp. 1765–1770. London, United Kingdom: (2015). https://doi.org/10.1109/iccw.2015.7247436
Le, H.T., Nguyen, D.V., Ngoc, N.P., Pham, A.T., Thang, T.C.: Buffer-based bitrate adaptation for adaptive HTTP streaming. In: Proceedings of IEEE Conf. on Advanced Technol. Commun., pp. 33–38. Hochiminh, Vietnam: (2013). https://doi.org/10.1109/atc.2013.6698072
Jiang, J., Sekar, V., Zhang, H.: Improving fairness, efficiency, and stability in http-based adaptive video streaming with festive. In: Proceedings of ACM Int. Conf. on Emerging Networking Experiments and Technol., pp. 97–108. Nice, France: (2012). https://doi.org/10.1145/2413176.2413189
Huang, T.Y., Johari, R., McKeown, N., Trunnell, M., Watson, M.: A buffer-based approach to rate adaptation: evidence from a large video streaming service. ACM SIGCOM Comput. Commun. Review. 44(4), 187–198 (2015). https://doi.org/10.1145/2619239.2626296
Rahman, W., Chung, K.: Chunk size aware buffer-based algorithm to improve viewing experience in dynamic HTTP streaming. IEICE Tran. Commun. E99-B(3), 767–775 (2016). https://doi.org/10.1587/transcom.2015ebp3398
Sieber, C., Hossfeld, T., Zinner, T., Tran-Gia, P., Timmerer, C.: Implementation and user-centric comparison of a novel adaptation logic for dash with SVC. In: Proceedings of IEEE Int. Symposium on Integrated Network Management, pp. 1318–1323. Ghent, Belgium: (2013). https://doi.org/10.1109/inm.2005.1440752
Dubin, R., Dvir, A., Hadar, O., Harel, N., Barkan, R.: Multicast adaptive logic for dynamic adaptive streaming over http network. In: Proceedings of IEEE Conf. on Comput. Commun. Workshops, pp. 269–274. Hong Kong: (2015). https://doi.org/10.1109/infcomw.2015.7179396
Dubin, R., Dvir, A., Pele, O., Hadar, O., Katz, I., Mashiach, O.: Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile users. Multimedia Syst. (2016). https://doi.org/10.1007/s00530-016-0525-6
Huang, T.Y., Nikhil, H., Brandon, H., Nick, M., Ramesh, J.: Confused, timid, and unstable: picking a video streaming rate is hard. In: Proceedings of ACM Int. Conf. on Internet Measurement, pp. 225–238. Boston, USA: (2012). https://doi.org/10.1145/2398776.2398800
Egger, S., Hossfeld, T., Schatz, R., Fiedler, M.: Waiting times in quality of experience for web based services. In: Proceedings of IEEE Int. Workshop on Quality Multimedia Experience, pp. 86–96. Melbourne, Australia: (2012). https://doi.org/10.1109/qomex.2012.6263888
Mueller, C., Stefan, L., Grandl, R., Timmerer, C.: Oscillation compensating dynamic adaptive streaming over HTTP. In: Proceedings of IEEE Int. Conf. on Multimedia and Expo, pp. 1–6. Torino, Italy: (2015). https://doi.org/10.1109/icme.2015.7177435
Moorthy, K., Choi, L.K., Bovik, A.C., De Veciana, G.: Video quality assessment on mobile devices: subjective, behavioral and objective studies. IEEE J. Sel. Topics Signal Process. 6(6), 652–671 (2012). https://doi.org/10.1109/jstsp.2012.2212417
Staelens, N., De Meulenaere, J., Claeys, M., Van Wallendael, G., Van den Broeck, W., De Cock, J., Van de Walle, R., Demeester, P., De Turck, F.: Subjective quality assessment of longer duration video sequences delivered over HTTP adaptive streaming to tablet devices. IEEE Trans. Broadcast. 60(4), 707–714 (2014). https://doi.org/10.1109/tbc.2014.2359255
Hoßfeld, T., Seufert, M., Sieber, C., Zinner, T.: Assessing effect sizes of influence factors towards a QoE model for HTTP adaptive streaming. In: Proceedings of IEEE Int. Conf. on Multimedia and Expo, pp. 111–116. Singapore: (2014). https://doi.org/10.1109/qomex.2014.6982305
Zink, M., Jens, S., Ralf, S.: Layer-encoded video in scalable adaptive streaming. IEEE Trans. Multimedia 7(1), 75–84 (2005). https://doi.org/10.1109/TMM.2004.840595
Zink, M., Künzel, O., Schmitt, J., Steinmetz, R.: Subjective Impression of Variations in Layer Encoded Videos. In: Proceeding of Int. Workshop on Quality of Service, pp. 137–154. Berkeley, CA, USA: (2003). https://doi.org/10.1007/3-540-44884-5_8
Grafl, M., Timmerer, C.: Representation switch smoothing for adaptive HTTP streaming. In: Proceedings of the Int. Workshop on Perceptual Quality of Systems, pp. 178–183. Vienna, Austria: (2013). https://doi.org/10.21437/PQS.2013-32
Zambelli, A.: Microsoft Corporation. IIS smooth streaming technical overview. [Online]. Available: https://docs.microsoft.com/en-us/iis/media/on-demand-smooth-streaming/smooth-streaming-technicaloverview. Accessed 10 Feb 2018
Adobe. Configure HTTP Dynamic Streaming and HTTP Live Streaming. [Online]. Available: https://helpx.adobe.com/adobe-media-server/dev/configure-dynamic-streaming-live-streaming.html. Accessed 10 Feb 2018
Pantos, R.: HTTP Live Streaming. [Online]. https://tools.ietf.org/html/rfc8216. Accessed 10 Feb 2018
Akhshabi, S., Anantakrishnan, L., Begen, A.C., Dovrolis, C.: What happens when HTTP adaptive streaming players compete for bandwidth?. In: Proceedings of ACM Workshop Netw. and Operating Syst. Support for Digital Audio and Video, pp. 9–14. Toronto, Canada: (2012). https://doi.org/10.1145/2229087.2229092
Jain, R., Chiu, D., Hawe, W.: A quantitative measure of fairness and discrimination for resource allocation in shared computer system. Technical Report, DEC, 1984
Acknowledgements
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00224, Development of generation, distribution and consumption technologies of dynamic media based on UHD broadcasting contents). It has also been conducted by the Research Grant of Kwangwoon University in 2018.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by M. Claypool.
Rights and permissions
About this article
Cite this article
Rahman, W.u., Chung, K. SABA: segment and buffer aware rate adaptation algorithm for streaming over HTTP. Multimedia Systems 24, 509–529 (2018). https://doi.org/10.1007/s00530-018-0588-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00530-018-0588-7