ABSTRACT Nowadays, it is crucial to provide a high quality of experience (QoE) for video streaming, and this is particularly challenging under fluctuating network conditions. Adaptive bitrate (ABR) algorithm is the core mechanism to optimize QoE under variable network bandwidth. However, existing ABRs may fall into sub‐optimization without considering video quality enhancement, which is incrementally employed to improve QoE after downloading. In this work, we observe that the degree of video quality enhancement (DVQE) varies across different video chunks with different bitrates, and thus propose the DVQE sensitivity‐aware adaptive bitrate algorithm (DSABR). Specifically, DSABR quantifies the DVQE sensitivity of each chunk bitrate by jointly considering its DVQE value and the corresponding chunk size, and accordingly selects the chunk bitrate with higher DVQE sensitivity. In this way, DSABR would achieve high QoE with minimal network bandwidth occupancy. Experimental results demonstrate the performance advantage of DSABR, especially under the conditions of limited network bandwidth and videos with large average DVQE and large DVQE variance. Specifically, under the real‐world network bandwidth dataset PUFFER, DSABR improves QoE by 94.0%, 133.7%, and 26.8% compared to the heuristic algorithms BOLA, FESTIVE, and RobustMPC, respectively. Furthermore, compared to the learning‐based algorithms COMYCO and MERINA, DSABR improves the QoE by 24.4% and 20.5%.
Hu et al. (Thu,) studied this question.