An Adaptive Bitrate Algorithm Based on Estimation and Video Adaptation for Improving QoE in DASH

摘要

Dynamic Adaptive streaming over HTTP (DASH) is widely used by content providers for video delivery and dominates traffic on cellular networks. The variation in both video bitrate and network bandwidth badly impacts on the user Quality of Experience (QoE), so recent works is going to submitting better design of DASH adaptation algorithms. In this work, an adaptive bitrate algorithm is proposed which incorporates the network state, the application state and the video variety conditions to adapt video quality under time varying wireless system. The proposed algorithm consists of two main units: estimation unit and video adaptation unit. During the estimation unit, a new attribute is included that scales the buffer occupancy estimation and the throughput estimation based on the variations in the current buffer level and measured throughput of previous download segments. While during the video adaptation unit, the selection of video bitrate is done based on both the measurements at estimation unit and a target level. The simulation results show that the proposed algorithm significantly outperforms the other rate adaptation algorithms in terms of providing maximum download bit rates, minimum number of bitrates switches and the maximum utilization of available bandwidth while maintaining the playback buffer level within limits without any playback interruptions.