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.
Another aspect of AMP being studied is the smoothness of transition between playout rate adjustment @cite_32 @cite_36 @cite_19 . The goal of these approaches is to ensure that adjustments made to the playout rate is done as smoothly as possible so as to reduce any noticeable effects to the viewers. We do not focus on rate smoothing in the current paper and again any smoothing scheme can be used within the framework.
@cite_36 @cite_19 @cite_32
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We propose a new scheme for streaming media systems that combines adaptive media playout (AMP) with rate-distortion (R-D)optimized packet transmission. AMP, the client-controlled, adaptive modification of the media playout rate, allows us to flexibly adjust the playout deadlines of individual packets, and can therefore reduce reconstruction distortion. This added flexibility incurs a subjective cost, however. We introduce functions that assess the subjective cost of a schedule of playout rate modifications, and we show how to optimize the schedule with respect to these costs and distortion. Because the optimal playout rate schedule and the R-D optimal transmission schedule are interdependent, we solve the two problems jointly. In simulations that model a receiver-driven scenario, results for a short media clip show a more than 2 dB improvement in mean PSNR for R-D optimized transmission scheduling combined with a moderate amount of AMP, over R-D optimized transmission scheduling alone. 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. Video streaming is one of the killer applications for cellular communications. The MPEG-4 fine-granularity scalability video coding technique can adapt to bandwidth variation and random packet errors. In this paper, to explore the impacts of cellular channel characteristics on the tolerance of buffer performance and quality of service, a novel statistical model-based adaptive media playout (AMP) is proposed by utilizing the statistical assumptions of both arrival and departure processes for a better decision on the dynamic threshold adjustment and frame-rate adjustment. Based on third-generation cellular transmission environment, simulation results will demonstrate that as compared to other AMP schemes, the proposed AMP control provides better visual quality with lower complexity. In this paper, we propose a server-client coordinated joint optimal frame selection with adaptive playout for delivering stored video under both limited channel bandwidth and finite client buffer condition. In particular, the client will reduce the frame playout rate whenever its buffer fullness level falls below a given threshold in an attempt to prevent buffer underflow. And when the buffer fullness exceeds the threshold, the client will switch back to the normal frame playout rate. The server is aware of the adaptive playout decision made by the client and incorporates the decision into its optimal frame selection framework for joint optimization. The objective is to minimize the number of frames that must be discarded in order to prevent client buffer underflow or overflow and make full use of the limited bandwidth resource.