Throughput Prediction Using Recurrent Neural Network Model
Bo Wei, Mayuko Okano, Kenji Kanai, Wataru Kawakami, Jiro Katto · 2018
To ensure good quality of experience for user when transmitting video content, throughput prediction can contribute to the selection of proper bitrate. In this paper, we propose a throughput prediction method with recurrent neural network (RNN) model. Experiments are conducted to evaluate the methods, and the results indicate that proposed method can decrease the prediction error by a maximum of 29.39% compared with traditional methods.