ARBITER+: Adaptive Rate-Based InTElligent HTTP StReaming Algorithm for Mobile Networks
Ahmed H. Zahran, Darijo Raca, Cormac J. Sreenan · IEEE Transactions on Mobile Computing · 2018
Dynamic adaptive streaming over HTTP (DASH) is widely adopted for video transport by major content providers. However, the inherent high variability in both encoded video and network rates represents a key challenge for designing efficient adaptation algorithms. Accommodating such variability in the adaptation logic design is essential for achieving a high user quality of Experience (QoE). In this paper, we present ARBITER+ as a novel adaptation algorithm for DASH. ARBITER+ integrates different components that are designed to ensure a high video QoE while accommodating inherent system variabilities. These components include a tunable adaptive target rate estimator, hybrid throughput sampling, controlled switching, and short-term actual video rate tracking. We extensively evaluate the streaming performance using real video and cellular network traces. We show that ARBITER+ components work in harmony to balance temporal and visual QoE aspects. Additionally, we show that ARBITER+ enjoys a noticeable QoE margin in comparison to state-of-the-art adaptation approaches in various operating conditions. Furthermore, we show that ARBITER+ also achieves the best application-level fairness when a group of mobile video clients shares a cellular base station.