A Fine-Tuned Control-Theoretic Approach for Dynamic Adaptive Streaming Over HTTP

Commercial implementations of adaptive streaming systems are either too aggressive or too conservative, not being able to efficiently deliver video content to the client. Because of these issues, a great number of adaptive streaming systems have been proposed in the academia. They employ different strategies, to select the proper video level that the server should send to the client. One trend is the use of control theory, because it guarantees system stability, and enables simulation and tuning of the system prior to its implementation. However, the current proposals that employ control theory do not take full advantage of this technique, because they do not thoroughly analyze the system parameters and their influence on the overall system performance. Therefore, it is possible that they use suboptimal solutions. In this paper, we propose a control-theoretic approach for selecting the video quality in a DASH environment. We use a controller added to a state machine, to improve the QoE and to maximize bandwidth utilization. We also present a comparison of several system settings performances, by changing the controller types, their gains, and the state machine parameters. Experimental results show the effectiveness of our proposed system for buffer time control and video level smoothness, and that it outperforms a current proposal in the academia.