基于预测机制的云媒体网络自适应视频流选择算法

研究移动网络中,如何进一步提高云媒体服务带宽利用率的问题,提出一种基于预测机制的云媒体网络自适应视频流选择算法。该算法包含可用带宽预测模型和视频流决策模型。在带宽预测模型中,根据带宽评估结果把当前的网络状态划分为三个模式,每个模式对应不同的带宽预测方法,并且不同的模式能够相互转化。在视频流决策模型中,利用预测的可用带宽,结合可伸缩视频编码技术为用户自适应的调整视频质量。根据实验,在不同网络环境下,该方法能够有效的利用带宽,并提高媒体服务质量。

Network-adaptive video stream selection algorithm based on prediction mechanism for cloud media

Research in mobile network, how to further improve the cloud media service bandwidth utilization problem. This paper developed a new prediction mechanism based on the cloud adaptive streaming media network selection algorithm. The proposed algorithm contains the available bandwidth prediction model and the video stream decision model. In the bandwidth prediction model, the current network state was divided into three modes according to the result of bandwidth evaluation, and each pattern was different from the bandwidth prediction method, and the different modes can be transformed into each other. In the video stream decision model, the use of the available bandwidth of the forecast, combined with scalable video encoding technology for the user to adjust the video quality. According to the experiment, this method can effectively utilize the bandwidth and improve the quality of media service under different network conditions.