Fresher Content or Smoother Playback? A Brownian-Approximation Framework for Real-Time Video Delivery in Wireless Networks
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This paper presents a Brownian-approximation framework to optimize the quality of experience (QoE) for real-time video delivery in wireless networks. In real-time video delivery, one major challenge is to tackle the natural tension between the two most critical QoE metrics: playback latency and video playback interruption. To study this trade-off, we first propose an analytical model that precisely captures all aspects of the playback process of a real-time video stream, including playback latency, video interruptions, and packet dropping. Built on this model, we show that the playback process of a real-time video can be approximated by a two-sided reflected Brownian motion. Through such Brownian approximation, we are able to study the fundamental limits of the two QoE metrics and characterize a necessary and sufficient condition for a set of QoE performance requirements to be feasible. We propose a simple scheduling policy that satisfies any feasible set of QoE performance requirements and then demonstrate the wide applicability of the proposed policy in network utility maximization for QoE. Finally, simulation results verify the accuracy of the proposed approximation and show that the proposed policy outperforms other popular baseline policies.
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