ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming

ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming

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Farzad Tashtarian (Alpen-Adria Universität Klagenfurt),  Abdelhak Bentaleb (Concordia University), Hadi Amirpour (Alpen-Adria Universität Klagenfurt)Sergey Gorinsky (IMDEA Networks Institute),  Junchen Jiang (University of Chicago), Hermann Hellwagner (Alpen-Adria-Universität Klagenfurt)Christian Timmerer (Alpen-Adria Universität Klagenfurt)

Live streaming of segmented videos over the Hypertext Transfer Protocol (HTTP) is increasingly popular and serves heterogeneous clients by offering each segment in multiple representations. A bitrate ladder expresses this choice as an ordered list of bitrate-resolution pairs. Whereas existing solutions for HTTP-based live streaming use a static bitrate ladder, the fixed ladders struggle to appropriately accommodate the dynamics in the video content and network-conditioned client capabilities. This paper proposes ARTEMIS as a practical scalable alternative that dynamically configures the bitrate ladder depending on the content complexity, network conditions, and clients’ statistics. ARTEMIS seamlessly integrates with the end-to-end streaming pipeline and operates transparently to video encoders and clients. We develop a cloud-based implementation of ARTEMIS and conduct extensive real-world and trace-driven experiments. The experimental comparison vs. existing prominent bitrate ladders demonstrates that live streaming with ARTEMIS outperforms all baselines, reduces encoding computation by 25%, end-to-end latency by 18%, and increases quality of experience (QoE) by 11%.

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