Joint Faces Scheduling and Bitrate Switching for Dynamic Adaptive Streaming over NDN Based on Stochastic Optimization

With the fast increase of video traffic transmitting over the Internet, dynamic adaptive streaming (DAS) has emerged as a conventional way for video streaming distribution. At the same time, Named Data Network (NDN) has been proposed to deal with various problems existed in the Internet. However, existing researches in DAS over NDN did not pay much attention to multihoming capability of NDN. Consumers who request data using multiple faces can aggregate bandwidth dof different links which results in choosing higher layers of the video, increasing the quality of video requested. Multiple faces streaming can also smoothen the throughput seen by the client, leading to less fluctuation of the layer switching. Moreover, applying multiple faces can decrease the risk of port failure, increase reliability of the system. In this paper, we propose a dynamic adaptive algorithm of joint faces scheduling and bitrate switching for video streaming request over NDN aiming at optimizing long-term quality of Quality of Experience (QoE) and the cost of consumers under a constraint of playback smoothness and fluctuation. The proposed algorithm is based on Lyapunov Optimization which does not need priori knowledge of the dynamic network state information for each port. Both our theoretical analysis as well as experiments show that this algorithm is effective.