一种基于多服务器的DASH客户端优化算法

A DASH Client Optimization Algorithm Based on Multiple Servers

在多服务器场景下,基于HTTP的动态自适应流媒体在传输过程中,由于用户请求的高度动态性及多服务器传输带宽的差异性,客户端获取的视频质量波动较频繁,影响到用户体验质量。针对上述问题,提出一种基于软件定义网络的视频分片请求调度算法。将多个分片组成一个视频块,利用分配策略把这多个分片分配至多个服务器,实现同一视频块内视频分片的码率同步,并使分片有序下载。同时,客户端算法采用Q学习方法,根据不同的环境状态决策出相应的码率。仿真实验结果表明,该算法可减少视频质量的波动,提高客户端平均视频质量。

In the transmission of Dynamic Adaptive Streaming over HTTP(DASH)for scenario,the client’s video quality would fluctuate much frequently due to the user’s high dynamic request and different transmission bandwidths of multiple servers.Such fluctuation would affect the Quality of Experience(QoE)seriously.To solve this problem,this paper proposes a video fragment request scheduling algorithm based on Software-Defined Network(SDN).By considering several video segments as one video block,these segments are assigned to a series of servers through an allocation strategy.This two-step method can not only realize the bit rate synchronization of the video segments in the same video block,but also enable the segments to be downloaded in an orderly manner.Furthermore,the client algorithm uses Q-learning method to deduce bit rate depending on different environmental state.Experimental results show that the proposed algorithm can reduce the fluctuation of video quality and improve the average video quality of the client.