HIGH EFFICIENCY LIVE VIDEO STREAMING WITH FRAME DROPPING

HTTP based video streaming is widely adopted in video service and its adaptive bitrate algorithms have attracted a lot of studies in recent years. However, most of the algorithms are designed for on-demand video service and are not suit- able for live video streaming service, which is sensitive to end-to-end latency. In this paper, we propose a live video streaming framework based on HTTP/2 which enables frame dropping for low latency environment. Firstly, we formulate live video streaming model and QoE model considering frame dropping. Then, an optimization problem is formulated aiming at high quality of video streaming. Furthermore, to solve this problem, we propose a live video streaming adaptation algorithm with frame dropping based on Model Predictive Control (MPC). Finally, extensive experiments are conducted to evaluate the proposed method over realistic traces with general ABR algorithms. Compared with the optimal solution, the proposed method achieves comparable performance with only 8.06% quality loss.