Neighbor Selection Strategies in the Wild for CDN/V2V WebRTC Live Streaming: Can we learn what a good neighbor is?
| Autor: | Ma, Zhejiayu, Rouibia, Soufiane, Giroire, Frederic, Urvoy-Keller, Guillaume |
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| Přispěvatelé: | Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA), Trident Media Guard [Saint-Sébastien-sur-Loire] (TMG), Trident Media Guard, Combinatorics, Optimization and Algorithms for Telecommunications (COATI), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-COMmunications, Réseaux, systèmes Embarqués et Distribués (Laboratoire I3S - COMRED), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), Signal, Images et Systèmes (Laboratoire I3S - SIS) |
| Rok vydání: | 2022 |
| Předmět: |
real deployment
[INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] hybrid P2P machine learning hybrid P2P live streaming peer selection machine learning real deployment A/B testing peer selection [INFO]Computer Science [cs] live streaming A/B testing [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] |
| Zdroj: | 2022 IEEE 47th Conference on Local Computer Networks (LCN) 2022 IEEE 47th Conference on Local Computer Networks (LCN), Sep 2022, Edmonton, France. pp.295-298, ⟨10.1109/LCN53696.2022.9843647⟩ |
| DOI: | 10.1109/lcn53696.2022.9843647 |
| Popis: | International audience; A hybrid CDN/Viewer-to-Viewer (V2V) architecture is an attractive solution for HTTP (HLS) and MPEG-DASHbased live streaming providers. It combines a traditional CDN with a V2V overlay for exchanging video fragments, reducing the cost of the CDN while maintaining the quality of experience. This work explores machine learning models to address the key challenge of neighbor selection. Our goal is to predict the connection quality between two arbitrary viewers using features such as locality, access providers, operating systems, past CDN, and V2V throughput. The proposed solutions are validated using an A/B testing approach on our production system, demonstrating a significant improvement in key system metrics compared to the traditional locality-based methods. We observe 17% higher V2V throughput, 26% lower delay, 37% fewer lost chunks, 39% fewer re-buffering, and 20% fewer quality switches. |
| Databáze: | OpenAIRE |
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