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.
@cite_36: Multimedia communications often require intramedia synchronization for video data to prevent potential playout discontinuity resulting from network delay variation (jitter) while still achieving satisfactory playout throughput. In this paper, we propose a neural network (NN) based intravideo synchronization mechanism, called the intelligent video smoother (IVS), operating at the application layer of the receiving end system. The IVS is composed of an NN traffic predictor, an NN window determinator, and a window-based playout smoothing algorithm. The NN traffic predictor employs an on-line-trained back-propagation neural network (BPNN) to periodically predict the characteristics of traffic modeled by a generic interrupted Bernoulli process (IBP) over a future fixed time period. With the predicted traffic characteristics, the NN window determinator determines the corresponding optimal window by means of an off-line-trained BPNN in an effort to achieve a maximum of the playout quality (Q) value. The window-based playout smoothing algorithm then dynamically adopts various playout rates according to the window and the number of packets in the buffer. Finally, we show that via simulation results and live video scenes, compared to two other playout approaches, IVS achieves high-throughput and low-discontinuity playout under a mixture of IBP arrivals.
@cite_19: 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.
@cite_32: 
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.