TL;DR
FastScan is a new low-complexity algorithm for HTTP video streaming that optimizes quality of experience by balancing playback rate and fairness, demonstrating superior robustness and performance over existing algorithms in real bandwidth conditions.
Contribution
The paper introduces FastScan, a novel, low-complexity rate adaptation algorithm that effectively handles dynamic bandwidth and imperfect predictions for improved streaming QoE.
Findings
FastScan reduces re-buffering time compared to state-of-the-art algorithms.
FastScan achieves higher average playback rates across diverse bandwidth traces.
FastScan demonstrates robustness in real cellular bandwidth scenarios.
Abstract
This paper proposes and evaluates a novel algorithm for streaming video over HTTP. The problem is formulated as a non-convex optimization problem which is constrained by the predicted available bandwidth, chunk deadlines, available video rates, and buffer occupancy. The objective is to optimize a QoE metric that maintains a tradeoff between maximizing the playback rate of every chunk and ensuring fairness among different chunks for the minimum re-buffering time. We propose FastScan, a low complexity algorithm that solves the problem. Online adaptations for dynamic bandwidth environments are proposed with imperfect available bandwidth prediction. Results of experiments driven by Variable Bit Rate (VBR) encoded video, video platform system (dash.js), and cellular bandwidth traces of a public dataset reveal the robustness of the online version of FastScan algorithm and demonstrate its…
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