ARBITER: Adaptive rate-based intelligent HTTP streaming algorithm

Abstract

Dynamic Adaptive streaming over HTTP (DASH) is widely used by content providers for video delivery and dominates traffic on cellular networks. The inherent variability in both video bitrate and network bandwidth negatively impacts the user Quality of Experience (QoE), motivating the design of better DASH-compliant adaptation algorithms. In this paper we present ARBITER, a novel streaming adaptation algorithm that explicitly integrates the variations in both video and network dynamics in its adaptation decisions. Our simulation-based performance evaluation, using real video content and cellular bandwidth traces, shows that ARBITER achieves an excellent tradeoff among streaming metrics in terms of received video quality, stall count, stall duration, and switching dynamics, leading to a relative improvement of 17-45% in user QoE in comparison to state-of-the-art algorithms