TY - JOUR
T1 - Adaptive media playout for low-delay video streaming over error-prone channels
AU - Kalman, Mark
AU - Steinbach, Eckehard
AU - Girod, Bernd
N1 - Funding Information:
Manuscript received April, 2001; revised October 2002. This work was supported in part by Intel Inc. and in part by the Stanford Networking Research Center. This paper was recommended by Associate Editor I. Lagendijk.
PY - 2004/6
Y1 - 2004/6
N2 - When media is streamed over best-effort networks, media data is buffered at the client to protect against playout interruptions due to packet losses and random delays. While the likelihood of an interruption decreases as more data is buffered, the latency that is introduced increases. In this paper we show how adaptive media playout (AMP), the variation of the playout speed of media frames depending on channel conditions, allows the client to buffer less data, thus introducing less delay, for a given buffer underflow probability. We proceed by defining models for the streaming media system and the random, lossy, packet delivery channel. Our streaming system model buffers media at the client, and combats packet losses with deadline-constrained automatic repeat request (ARQ). For the channel, we define a two-state Markov model that features state-dependent packet loss probability. Using the models, we develop a Markov chain analysis to examine the tradeoff between buffer underflow probability and latency for AMP-augmented video streaming. The results of the analysis, verified with simulation experiments, indicate that AMP can greatly improve the tradeoff, allowing reduced latencies for a given buffer underflow probability.
AB - When media is streamed over best-effort networks, media data is buffered at the client to protect against playout interruptions due to packet losses and random delays. While the likelihood of an interruption decreases as more data is buffered, the latency that is introduced increases. In this paper we show how adaptive media playout (AMP), the variation of the playout speed of media frames depending on channel conditions, allows the client to buffer less data, thus introducing less delay, for a given buffer underflow probability. We proceed by defining models for the streaming media system and the random, lossy, packet delivery channel. Our streaming system model buffers media at the client, and combats packet losses with deadline-constrained automatic repeat request (ARQ). For the channel, we define a two-state Markov model that features state-dependent packet loss probability. Using the models, we develop a Markov chain analysis to examine the tradeoff between buffer underflow probability and latency for AMP-augmented video streaming. The results of the analysis, verified with simulation experiments, indicate that AMP can greatly improve the tradeoff, allowing reduced latencies for a given buffer underflow probability.
KW - Markov model
KW - Multimedia communication
KW - Scalable media
KW - Streaming
KW - Time-scale modification
UR - http://www.scopus.com/inward/record.url?scp=2942631158&partnerID=8YFLogxK
U2 - 10.1109/TCSVT.2004.828335
DO - 10.1109/TCSVT.2004.828335
M3 - Article
AN - SCOPUS:2942631158
SN - 1051-8215
VL - 14
SP - 841
EP - 851
JO - IEEE Transactions on Circuits and Systems for Video Technology
JF - IEEE Transactions on Circuits and Systems for Video Technology
IS - 6
ER -