ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming

Authors: 

Farzad Tashtarian, Christian Doppler Laboratory ATHENA, Alpen-Adria Universität Klagenfurt; Abdelhak Bentaleb, Concordia University; Hadi Amirpour, Christian Doppler Laboratory ATHENA, Alpen-Adria Universität Klagenfurt; Sergey Gorinsky, IMDEA Networks Institute; Junchen Jiang, University of Chicago; Hermann Hellwagner and Christian Timmerer, Christian Doppler Laboratory ATHENA, Alpen-Adria Universität Klagenfurt

Abstract: 

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 by 11%.

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BibTeX
@inproceedings {295533,
author = {Farzad Tashtarian and Abdelhak Bentaleb and Hadi Amirpour and Sergey Gorinsky and Junchen Jiang and Hermann Hellwagner and Christian Timmerer},
title = {{ARTEMIS}: Adaptive Bitrate Ladder Optimization for Live Video Streaming},
booktitle = {21st USENIX Symposium on Networked Systems Design and Implementation (NSDI 24)},
year = {2024},
isbn = {978-1-939133-39-7},
address = {Santa Clara, CA},
pages = {591--611},
url = {https://www.usenix.org/conference/nsdi24/presentation/tashtarian},
publisher = {USENIX Association},
month = apr
}