Markov Based Rate Adaption Approach for Live Streaming over HTTP/2

Release Date:2018-07-18 Author:XIE Lan, ZHANG Xinggong , HUANG Cheng, and DONG Zhenjiang Click:

[Abstract] Dynamic adaptive streaming over HTTP (DASH) has been widely deployed. However, large latency in HTTP/1.1 cannot meet the requirements of live streaming. Data⁃pushing in HTTP/2 is emerging as a promising technology. For video live over HTTP/2, new challenges arise due to both low⁃delay and small buffer constraints. In this paper, we study the rate adaption problem over HTTP/2 with the aim to improve the quality of experience (QoE) of live streaming. To track the dynamic characteristics of the streaming system, a Markov⁃theoretical approach is employed. System variables are taken into account to describe the system state, by which the system transition probability is derived. Moreover, we design a dynamic reward function considering both the quality of user experience and dynamic system variables. Therefore, the rate adaption problem is formulated into a Markov decision based optimization problem and the best streaming policy is obtained. At last, the effectiveness of our proposed rate adaption scheme is demonstrated by numerous experiment results.

[Keywords] DASH; live; rate adaption; Markov decision

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