Perceptual Content-Aware Bitrate Adaptation for HTTP Streaming using Markov Decision Process
Xue Jiang, Yuan Zhang · 2021
This paper presents a perceptual content-aware bitrate adaptation algorithm for the HTTP streaming services. Compared with the traditional throughput-based and buffer-based algorithms, the impact of visual perception on user's Quality of Experience (QoE) has also been considered. We model the content-aware bitrate adaptation problem into a Markov Decision Process (MDP) and develop a segmented value iteration method to solve this problem. We have integrated this adaptive algorithm into dash.js, on which we can compare our approach with the default throughput-based algorithm and well-known BOLA algorithm. The results have shown that our algorithm can not only reach the higher average quality on the premise of maintaining fluency but also enable the scenes with higher attention to obtain higher quality, thus ultimately improve QoE.