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.
Coalition Game-based Approach for Improving the QoE of DASH-based Streaming in Multi-servers Scheme
HTTP动态自适应流媒体（Dynamic Adaptive Streaming over HTTP，DASH）正在成为大规模有效视频流量交付的事实方法，其首要成功因素是赋予流媒体客户端完全的自主权，使其更加智能，并在基于拉取的范式下实现粒度视频块的分散式视频质量决策逻辑。然而，客户端的纯粹自主性本质上导致了整体自私的环境，其中每个客户端独立地努力提高其体验质量（QoE）。因此，客户端会伤害对方，包括自己，由于他们的感知范围有限。这个缺点可以通过采用一种机制，具有全局视图，从而可以有效地管理可用资源来解决。在本文中，我们提出了一个基于博弈论的方法来解决多服务器设置中的客户端的自私问题，而不影响其自治。特别地，我们采用联盟博弈框架来影响客户端到最好的服务器，最终最大限度地提高客户端的整体平均质量，同时防止重新缓冲。我们通过大量的实验验证了我们的解决方案，并展示了所提出的解决方案的有效性。
