SATE: Providing Stable and Agile Adaptation in HTTP-Based Video Streaming

Online video streaming service, such as Youtube and Netflix, is emerging as a killer application that constitutes most IP traffic. Users want high-quality video streaming service; however, network bandwidth cannot keep up user's demand. In the HTTP-based video streaming technology, the video provider divides the video into multiple chunks, encodes it at various bitrates, and stores it in the media server. The client requests a video chunk using an adaptive bitrate (ABR) algorithm, considering the network conditions. While there are many works to maximize user satisfaction, the state-of-the-art ABR algorithms are still vulnerable to rebuffering due to inaccurate estimates and decisions. To address this problem, we first analyze the real-world traces and find several design inferences for an efficient ABR algorithm. Then, we introduce SATE, an ABR algorithm that provides a stable and agile adaptation even in bandwidth constraint and dramatically changing network conditions. We evaluate the performance of SATE in various network settings and demonstrate its efficacy in practice. SATE provides a stable adaptation and dramatically reduced rebuffering while delivering a similar average bitrate compared to the state-of-the-art ABR algorithms.