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RLive: Robust Delivery System for Scaling Live Streaming Services

Yu Tian, Gerui Lv, Qinghua Wu, Ruili Fang, Yajie Peng, Zhichen Xue, Rui Han, Chuanqing Lin, Xiaofei Pang, Ri Lu, Zhenyu Li

2026Year

Abstract

As the demand for streaming services surges, content delivery network (CDN) operators face increasing pressure to scale live video delivery without proportionally increasing infrastructure costs. While best-effort edge resources offer a cost-effective extension to traditional CDN capacity, their limited bandwidth and unstable performance pose significant challenges. Our operational experience shows that naively layering such resources onto existing CDN infrastructure falls short in meeting performance and scalability demands. This paper presents RLive, a robust delivery system that scales CDN capacity by integrating best-effort edge resources. RLive features a redundancy-free multi-source data plane to support reliable and cost-efficient live streaming, along with a multi-layer collaborative control plane that combines the global view with local adaptability for scalable user-to-node mapping. Deployed in ByteDance CDN to support large-scale live streaming services with hundreds of millions of daily viewers, RLive has tripled delivery capacity while reducing rebuffering events by 14.9–20.1%.

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