基于模糊控制的流媒体自适应传输算法

基于HTTP的动态自适应流媒体DASH传输协议可以使用户根据自身的终端显示能力和信道条件选择合适的视频质量，是网络视频服务技术的发展方向。如何根据网络吞吐量的变化自适应地选择视频码率，以获得最佳的用户体验质量QOE，在已有的DASH系统中还没有得到很好的解决。 提出了一种基于模糊控制的自适应传输算法，将缓存的视频余量以及用户申请的视频码率和网络吞吐量的码率失配度作为输入，将预期的缓存变化量作为输出,通过模糊逻辑实现以下控制目的：(1）将缓存稳定在一个安全的区间；(2）使传输视频的平均质量最大化；(3）避免因带宽波动所造成的视频播放中断。最后，分别在两种虚拟网络环境和两种实际网络环境下进行性能测试，实验结果表明，与已有的算法相比较，本文提出的算法可以给用户带来更好的QOE。

An adaptive video streaming transmission algorithm based on fuzzy control

Adaptive Streaming over HTTP (DASH) transmission protocol based on HTTP can enable users to select suitable video quality according to their terminal display capabilities and channel conditions, which is the development direction of network video service technology. How to adaptively select the video bit rate to obtain the best Quality of Experience (QOE) according to the change of network throughput has not been well solved in the existing DASH systems. In this paper, an adaptive transmission algorithm based on fuzzy control is proposed, which takes the buffered video time and the bitrate mismatch between the video bitrate and the network throughput as input and the expected buffer change as output. Fuzzy logic is used to achieves the following control objectives: (1) The buffered video time stays within a safe range; (2) the average quality of the transmitted video is maximized, and (3) the video playback interruption caused by bandwidth fluctuation is avoided. Finally, performance tests were conducted in two virtual network environments and two actual network environments. The experimental results show that the proposed algorithm is superior to traditional algorithms in terms of QOE.