ARTEMIS: Adaptive Bitrate Ladder Optimization for Live Video Streaming
Farzad Tashtarian, Abdelhak Bentaleb, Hadi Amirpour, Sergey Gorinsky, Junchen Jiang, Hermann Hellwagner, Christian Timmerer
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 a 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 baseline solutions, reduces encoding computation by 25%, end-to-end latency by 18%, and increases the quality of experience by 11%.
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Cited by top-tier papers7
- ALPHAS: Adaptive Bitrate Ladder Optimization for Multi-Live Video StreamingFarzad Tashtarian, Mahdi Dolati, Daniele Lorenzi, Mojtaba Mozhganfar et al.INFOCOM 2025 · 5 citations
- Roaming Free in the VR World with MP2Yifei Xu, Xumiao Zhang, Yuning Chen, Pan Hu et al.USENIX ATC 2025 · 2 citations
- CardioLive: Empowering Video Streaming with Online Cardiac Monitoring via Audio-Visual LearningSheng Lyu, Ruiming Huang, Sijie Ji, Yasar Abbas Ur Rehman et al.ACM MM 2025 · 1 citation
- Camel: Frame-Level Bandwidth Estimation for Low-Latency Live Streaming under Video Bitrate UndershootingLiming Liu, Zhidong Jia, Li Jiang, Wei Zhang et al.WWW 2026
- Medley: Optimizing Midgress Bandwidth for Commercial Live Streaming CDNsHaiping Wang, Wanxin Shi, Sandesh Dhawaskar Sathyanarayana, Shu Shi et al.NSDI 2026
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