You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
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.

Cited Abstract(s):
[1]: 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.

[2]: 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.
[2] and [1] both examined the trade-off between delay and buffer underflow using a two state Markov models. further proposed AMP-Initial, AMP-Robust and AMP-Live. AMP-Initial slows down the playout rate until the buffer reaches a certain target level, this produces a lower perceived initial buffering delay to the viewer. AMP-Robust slowdowns the playout rate if the current buffer occupancy falls below the target buffer level while AMP-Live slowdowns or speedups the playout rate to maintain the target buffer level.