This paper aims to reduce the prebuffering requirements, while maintaining continuity, for video streaming. Current approaches do this by making use of adaptive media playout (AMP) to reduce the playout rate. However, this introduces playout distortion to the viewers and increases the viewing latency. We approach this by proposing a frame rate optimization framework that adjusts both the encoder frame generation rate and the decoder playout frame rate. Firstly, we model this problem as the joint adjustment of the encoder frame generation interval and the decoder playout frame interval. This model is used with a discontinuity penalty virtual buffer to track the accumulated difference between the receiving frame interval and the playout frame interval. We then apply Lyapunov optimization to the model to systematically derive a pair of decoupled optimization policies. We show that the occupancy of the discontinuity penalty virtual buffer is correlated to the video discontinuity and that this framework produces a very low playout distortion in addition to a significant reduction in the prebuffering requirements compared to existing approaches. Secondly, we introduced a delay constraint into the framework by using a delay accumulator virtual buffer. Simulation results show that the the delay constrained framework provides a superior tradeoff between the video quality and the delay introduced compared to the existing approach. Finally, we analyzed the impact of delayed feedback between the receiver and the sender on the optimization policies. We show that the delayed feedbacks have a minimal impact on the optimization policies.
Prebuffering video data has been studied in @cite_0 @cite_16 @cite_40 . These techniques are focused on calculating the correct amount of prebuffered data based on a mathematical model to avoid the occurrence of a buffer underflow once the video playout has started. However, these techniques do not take into account of the varying playout rates and the resulting reduction in prebuffering into their models. Furthermore, prebuffering introduces unwanted delay into the system and is known to have an impact on the user perceived quality of the video @cite_14 .
@cite_0 @cite_14 @cite_40 @cite_16
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Network variations in video streaming require sufficient data to be prebuffered at the client prior to playout. This receiver buffer prevents the display process from starvation in case of network congestion. Prebuffering, however, is also responsible for the major part of the delay between requesting a media stream and playing it at the receiver. We show how adaptive media playout can be employed to reduce the delay introduced by the receiver buffer while preserving the same resilience against buffer underflow as in non-adaptive media playout. For adaptive media playout we adjust the playout speed of the media packets depending on the condition of the channel and the current client buffer fullness. We employ a two-state Markov channel model to analyze the buffer underflow-delay trade-off for our adaptive playout strategy and show that for typical parameters the average end-to-end delay can be reduced by 1 to 2 seconds. We study the optimal streaming of variable bit-rate (VBR) video over a random VBR channel. The goal of a streaming application is to enable the successful decoding of each video object before its displaying deadline is violated. Hence, we define the main performance metric of a streaming system as the probability of un-interrupted video presentation, or jitter-free probability. Previous literature has described solutions to estimate the jitter-free probability by assuming either independence in the encoded data process or simplistic channel models. In this work, we present a novel analytical framework, which requires only some basic statistical information of an arbitrary VBR channel, to bound the probability of jitter-free playout under the constraint of initial playout delay and receiver buffer size. Both the infinite and finite buffer cases are considered. This technique is then applied to investigate streaming over a wireless system modeled by an extended Gilbert channel with ARQ transmission control. Experimental results with MPEG-4 VBR encoded video demonstrates that the proposed analysis derives close bounds to the actual system performance. Finally, we show that the proposed analysis provides a theoretical foundation to quantify the tradeoffs between the initial playout delay, the receiver buffer size, and the jitter-free probability for a general class of VBR streaming over random VBR channels. 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. We present a high-performance prefetching protocol for the delivery of prerecorded VBR video from a server across a packet-switched network to a large number of clients. Not only does the protocol give constant perceptual quality and almost 100 link utilization, but it also allows for immediate commencement of the video upon user request and near instantaneous response to pause resume and temporal jumps. The protocol requires: (1) that each client have a small amount of memory dedicated to the application; (2) that there is one bottleneck shared link between the server and the clients. Our protocol is based on the observation that there are frequent periods of time during which the shared link's bandwidth is under utilized. During these periods the server can prefetch frames from any of the ongoing videos and can send the frames to the buffers in the appropriate clients. The server chooses prefetched frames according to a join-the-shortest-queue policy. We present simulation results of our prefetch policy that are based on MPEG encoded traces.