Buffer-Based Adaptive Bitrate Algorithm for Enhanced Quality of Experience

Video streaming has become a popular method for delivering video content over the Internet, and the number of users and video content is increasing rapidly. The user's quality of experience (QoE) is a crucial factor in the success of video streaming services, as it quantifies the user's satisfaction. The QoE is affected by the video quality, starvation instants, and quality switching. To maximize the QoE, adaptive bitrate (ABR) algorithms select the video quality based on the network conditions and the client's buffer capacity. In this paper, a buffer-based ABR algorithm is proposed to maximize the user's QoE by minimizing the duration and frequency of starvation events and the time spent at the lowest quality level while maintaining smooth quality switching. A SimEvents-based scalable video coding SVC dynamic adaptive streaming over HTTP (DASH) system is developed to simulate the proposed algorithm. The performance of the proposed algorithm is compared to that of a baseline algorithm under different network conditions, and it is shown that the proposed algorithm outperforms the baseline algorithm in terms of buffer occupancy, quality switching and video quality.