An evaluation of buffer- and rate-based HTTP Adaptive Streaming strategies

Video streaming has become an indispensable technology in people's lives. However, the variability and instability of network conditions poses one of the biggest challenges to video streaming. In this paper, we study HTTP Adaptive Streaming (HAS), a technology that relieves these issues by adapting the video reproduction to the current network conditions. More specifically, we classify HAS strategies and evaluate buffer-based and rate-based solutions both independently and in combination with each other. Our simulations demonstrate that buffer-based policies offer better results in terms of Quality of Experience (QoE) metrics such as quality layer selection and frequency of quality switches, while rate-based policies lead to less video stallings.