Client intelligence for adaptive streaming solutions

In state-of-the-art adaptive streaming solutions, to cope with varying network conditions, the client side can switch between several video copies encoded at different bit-rates during streaming. Each video file version is divided into chunks of equal duration. To achieve continuous video playback, each chunk needs to arrive at the client before its playback deadline. The perceptual quality of a chunk increases with the chunk size in bits, whereas bigger chunks require more transmission time. Therefore, there is a tradeoff between the overall video quality and continuous playback, which can be optimized by proper selection of the next chunk from the encoded versions. This paper proposes a method to compute a set of optimal client strategies for this purpose.

[1]  Martin L. Puterman,et al.  Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .

[2]  A. Murat Tekalp,et al.  Delay-Distortion Optimization for Content-Adaptive Video Streaming , 2007, IEEE Transactions on Multimedia.

[3]  Martin Vetterli,et al.  Receiver-driven layered multicast , 1996, SIGCOMM 1996.

[4]  Nicolas D. Georganas,et al.  Adaptive video transcoding and streaming over wireless channels , 2005, J. Syst. Softw..

[5]  Engelbertus Wilhelmus Hesselman Distribution of multimedia streams to mobile internet users , 2005 .

[6]  Miska M. Hannuksela,et al.  Semi-Fuzzy Rate Controller for Variable Bit Rate Video , 2008, IEEE Transactions on Circuits and Systems for Video Technology.

[7]  Marie-Line Alberi-Morel,et al.  Performance Evaluation of Channel Change for DVB-SH Streaming Services , 2010, 2010 IEEE International Conference on Communications.

[8]  Mathias Johanson A RTP to HTTP video gateway , 2001, WWW '01.

[9]  Shu-Ching Chen,et al.  Video streaming over the internet with optimal bandwidth resource allocation , 2008, Multimedia Tools and Applications.

[10]  Deborah Estrin,et al.  Conference proceedings on Applications, technologies, architectures, and protocols for computer communications , 1996, SIGCOMM 1996.

[11]  Martin Reisslein,et al.  Adaptive bitstream switching of scalable video , 2007, Signal Process. Image Commun..

[12]  Jong Hyuk Park,et al.  A scalable and adaptive video streaming framework over multiple paths , 2010, Multimedia Tools and Applications.

[13]  C.-C. Jay Kuo,et al.  Buffer-constrained R-D optimized rate control for video coding , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[14]  Jenq-Shiou Leu,et al.  Practical design of a proxy agent to facilitate adaptive video streaming service across wired/wireless networks , 2009, J. Syst. Softw..

[15]  Carsten Griwodz,et al.  Frequent layer switching for perceived quality improvements of coarse-grained scalable video , 2010, Multimedia Systems.

[16]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[17]  Yue Lu,et al.  Assessing the Quality of Experience of SopCast , 2009, Int. J. Internet Protoc. Technol..

[18]  Ralf Steinmetz,et al.  Subjective impression of variations in layer encoded videos , 2003, IWQoS'03.

[19]  Bo Li,et al.  Coolstreaming: Design, Theory, and Practice , 2007, IEEE Transactions on Multimedia.

[20]  A. Murat Tekalp,et al.  Per-GOP Bitrate Adaptation for H.264 Compressed Video Sequences , 2005, VLBV.

[21]  Wen Gao,et al.  Rate control for JVT video coding scheme with HRD considerations , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[22]  Yong-Hyun Kim,et al.  A Buffer-Controlled Adaptive Video Streaming for Mobile Devices , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).

[23]  Wim F. J. Verhaegh,et al.  Quality Control for Scalable Media Processing Applications , 2004, J. Sched..