Abstract
A lot of people around the world commute using public transportation and would like to spend this time viewing streamed video content such as news or sports updates. However, mobile wireless networks typically suffer from severe bandwidth fluctuations, and the networks are often completely unresponsive for several seconds, sometimes minutes. Today, there are several ways of adapting the video bitrate and thus the video quality to such fluctuations, for example, using scalable video codecs or segmented adaptive HTTP streaming that switches between nonscalable video streams encoded in different bitrates. Still, for a better long-term video playout experience that avoids disruptions and frequent quality changes while using existing video adaptation technology, it is desirable to perform bandwidth prediction and planned quality adaptation.
This article describes a video streaming system for receivers equipped with a GPS. A receiver's download rate is constantly monitored, and periodically reported back to a central database along with associated GPS positional data. Thus, based on the current location, a streaming device can use a GPS-based bandwidth-lookup service in order to better predict the near-future bandwidth availability and create a schedule for the video playout that takes likely future availability into account. To create a prototype and perform initial tests, we conducted several field trials while commuting using public transportation. We show how our database has been used to predict bandwidth fluctuations and network outages, and how this information helps maintain uninterrupted playback with less compromise on video quality than possible without prediction.
Supplemental Material
Available for Download
Supplemental movie, appendix, image and software files for, Video streaming using a location-based bandwidth-lookup service for bitrate planning.
- Adobe. 2010. HTTP dynamic streaming on the Adobe Flash platform. http://www.adobe.com/products/httpdynamicstreaming/pdfs/httpdynamicstreaming_wp_ue.pdf.Google Scholar
- Akamai. 2010. Akamai HD for iPhone encoding best practices. http://www.akamai.com/dl/whitepapers/Akamai_HDNetwork_Encoding_BP_iPhone_iPad.pdf.Google Scholar
- Brandt, J. and Wolf, L. 2008. Adaptive video streaming for mobile clients. In Proceedings of the ACM International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV). 113--114. Google Scholar
Digital Library
- Curcio, I. D. D., Vadakital, V. K. M., and Hannuksela, M. M. 2010. Geo-predictive real-time media delivery in mobile environment. In Proceedings of the ACM Multimedia International Conference. 3--8. Google Scholar
Digital Library
- Diaz-Zayas, A., Merino, P., Panizo, L., and Recio, A. M. 2007. Evaluating video streaming over GPRS/UMTS networks: A practical case. In Proceedings of the IEEE Vehicular Technology Conference (VTC). 624--628.Google Scholar
- Evensen, K., Kupka, T., Kaspar, D., Halvorsen, P., and Griwodz, C. 2010. Quality-adaptive scheduling for live streaming over multiple access networks. In Proceedings of the ACM International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV). 21--26. Google Scholar
Digital Library
- Goyal, V. K. 2001. Multiple description coding: Compression meets the network. IEEE Signal Proce. Mag. 18, 5, 74--93.Google Scholar
- Guo, M., Ammar, M. H., and Zegura, E. W. 2005. V3: A vehicle-to-vehicle live video streaming architecture. Pervas. Mobile Comput. 1, 4, 404--424. Google Scholar
Digital Library
- Horsmanheimo, S., Jormakka, H., and Lähteenmäki, J. 2004. Location-aided planning in mobile network—trial results. Wirel. Personal Comm. 30, 207--216. Google Scholar
Digital Library
- Hsu, C.-H. and Hefeeda, M. 2010. Achieving viewing time scalability in mobile video streaming using scalable video coding. In Proceedings of the ACM Multimedia International Conference. 111--122. Google Scholar
Digital Library
- Huang, J., Krasic, C., Walpole, J., and Feng, W. 2003. Adaptive live video streaming by priority drop. In Proceedings of the IEEE International Conference on Advanced Video and Signal-Besed Surveillance. 342--347. Google Scholar
Digital Library
- Johansen, D., Johansen, H., Aarflot, T., Hurley, J., Kvalnes, Â., Gurrin, C., Sav, S., Olstad, B., Aaberg, E., Endestad, T., Riiser, H., Griwodz, C., and Halvorsen, P. 2009. DAVVI: A prototype for the next generation multimedia entertainment platform. In Proceedings of the ACM Multimedia International Conference. 989--990. Google Scholar
Digital Library
- Kaspar, D., Evensen, K., Engelstad, P. E., Hansen, A. F., Halvorsen, P., and Griwodz, C. 2010. Enhancing video-on-demand playout over multiple heterogeneous access networks. In Proceedings of the IEEE Consumer Communications and Networking Conference (CCNC). 47--51. Google Scholar
Digital Library
- Krasic, C., Walpole, J., and Feng, W.-c. 2003. Quality-adaptive media streaming by priority drop. In Proceedings of the ACM International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV). 112--121. Google Scholar
Digital Library
- Lee, K. C., Navarro, J. M., Chong, T. Y., Lee, U., and Gerla, M. 2010. Trace-based evaluation of rate adaptation schemes in vehicular environments. In Proceedings of the IEEE Vehicular Technology Conference (VTC).Google Scholar
- Liva, G., Diaz, N. R., Scalise, S., Matuz, B., Niebla, C. P., Ryu, J.-G., Shin, M.-S., and Lee, H.-J. 2008. Gap filler architectures for seamless DVB-S2/RCS provision in the railway environment. In Proceedings of the IEEE Vehicular Technology Conference (VTC). 2996--3000.Google Scholar
- Mähönen, P., Petrova, M., Riihijärvi, J., and Wellens, M. 2006. Cognitive wireless networks: your network just became a teenager. In Proceedings of IEEE INFOCOM.Google Scholar
- Mai, C.-H., Huang, Y.-C., and Wei, H.-Y. 2010. Cross-layer adaptive H.264/AVC streaming over IEEE 802.11e experimental testbed. In Proceedings of the IEEE Vehicular Technology Conference (VTC).Google Scholar
- Move Networks. 2008. Internet television: Challenges and opportunities. Tech. rep., Move Networks, Inc.Google Scholar
- Netview Technology. 2010. http://www.netview.no/index.php?page=downloader.Google Scholar
- Ni, P., Eichhorn, A., Griwodz, C., and Halvorsen, P. 2009. Fine-grained scalable streaming from coarse-grained videos. In Proceedings of the ACM International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV). 103--108. Google Scholar
Digital Library
- Pantos, R., Batson, J., Biderman, D., May, B., and Tseng, A. 2010. HTTP live streaming. http://tools.ietf.org/html/draft-pantos-http-live-streaming-04.Google Scholar
- Rejaie, R. and Ortega, A. 2003. PALS: peer-to-peer adaptive layered streaming. In Proceedings of the International Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV). 153--161. Google Scholar
Digital Library
- Riiser, H., Halvorsen, P., Griwodz, C., and Hestnes, B. 2008. Performance measurements and evaluation of video streaming in HSDPA networks with 16QAM modulation. In Preceedings of IEEE ICME. 489--492.Google Scholar
- Riiser, H., Halvorsen, P., Griwodz, C., and Johansen, D. 2010. Low overhead container format for adaptive streaming. In Proceedings of the ACM Multimedia International Conference. 193--198. Google Scholar
Digital Library
- Schierl, T., de la Fuente, Y. S., Globisch, R., Hellge, C., and Wiegand, T. 2010. Priority-based media delivery using SVC with RTP and HTTP streaming. Multimed. Tools Appl. (MTAP), 1--20. Google Scholar
Digital Library
- Schwarz, H., Marpe, D., and Wiegand, T. 2007. Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Trans. Circ. Syst. for Video Tech. 17, 9, 1103--1129. Google Scholar
Digital Library
- Sun, J.-Z., Sauvola, J., and Riekki, J. 2005. Application of connectivity information for context interpretation and derivation. In Proceedings of ConTEL. 303--310.Google Scholar
- Tamai, M., Sun, T., Yasumoto, K., Shibata, N., and Ito, M. 2004. Energy-aware QoS adaptation for streaming video based on MPEG-7. In Proceedings of IEEE ICME. 189--192.Google Scholar
- Wac, K., van Halteren, A., and Konstantas, D. 2006a. Qos-predictions service: Infrastructural support for proactive qos- and context-aware mobile services (position paper). Lecture Notes in Computer Science, vol. 4278, Springer. 1924--1933. Google Scholar
Digital Library
- Wac, K., van Halteren, A., and Konstantas, D. 2006b. QoS-predictions service: Infrastructural support for proactive QoS- and context-aware mobile services (position paper). In Proceedings of OTM Workshops. 1924--1933. Google Scholar
Digital Library
- Zambelli, A. 2009. Smooth streaming technical overview. http://learn.iis.net/page.aspx/626/smooth-streaming-technical-overview/.Google Scholar
- Zink, M., Künzel, O., Schmitt, J., and Steinmetz, R. 2003. Subjective impression of variations in layer encoded videos. In Proceedings of the IEEE International Workshop on Quality of Service. 137--154. Google Scholar
Digital Library
Recommendations
Commute path bandwidth traces from 3G networks: analysis and applications
MMSys '13: Proceedings of the 4th ACM Multimedia Systems ConferenceIn this dataset paper, we present and make available real-world measurements of the throughput that was achieved at the application layer when adaptive HTTP streaming was performed over 3G networks using mobile devices. For the streaming sessions, we ...
A comparison of quality scheduling in commercial adaptive HTTP streaming solutions on a 3G network
MoVid '12: Proceedings of the 4th Workshop on Mobile VideoThere are many available commercial streaming solutions that perform quality adaption. An important issue with respect to users' perceived quality is how the system schedules the quality levels to match the available network resources. In this study, we ...
MASERATI: mobile adaptive streaming based on environmental and contextual information
WiNTECH '13: Proceedings of the 8th ACM international workshop on Wireless network testbeds, experimental evaluation & characterizationWireless/mobile video streaming has become increasingly popular, which makes wireless link bandwidth scarce. To provide streaming services to mobile users, it is crucial to adapt to the link condition and traffic fluctuation. We investigate which ...






Comments