Delay-Rate-Distortion Optimization for Cloud Gaming With Hybrid Streaming

Cloud gaming, as the emerging game service, has attracted significant attentions. However, traditional video streaming approach suffers from high bandwidth consumption, and traditional graphics streaming approach requires a long initial period to download game models. In this paper, we propose a novel hybrid streaming framework, jointly applying video streaming and graphics streaming to provide a high quality gaming experience. In the proposed framework, cloud servers not only transmit the encoded video frames, but also progressively transmit the graphics data, which are used to render a game frame to provide an additional reference to video encoder. Based on the proposed framework, we investigate the delay-RateDistortion (d-R-D) optimization problem, where the source rate between the video stream and the graphics stream is optimized to minimize the overall distortion under the bandwidth and response delay constraints. Experimental results demonstrate that the proposed hybrid streaming can achieve the lowest distortion under the constraints of bandwidth and response delay, compared to the traditional video streaming and graphics streaming.