Large-scale video streaming events attract millions of simultaneous viewers, stressing existing delivery infrastructures. Client-driven adaptation reacts slowly to shared congestion, while server-based coordination introduces scalability bottlenecks and single points of failure. We present COMETS, a coordinated multi-destination video transmission framework that leverages information-centric networking principles such as request aggregation and in-network state awareness to enable scalable, fair, and adaptive rate control. COMETS introduces a novel range-interest protocol and distributed in-network decision process that aligns video quality across receiver groups while minimizing redundant transmissions. To achieve this, we develop a lightweight distributed optimization framework that guides per-hop quality adaptation without centralized control. Extensive emulation shows that COMETS consistently improves bandwidth utilization, fairness, and user-perceived quality of experience over DASH, MoQ, and ICN baselines, particularly under high concurrency. The results highlight COMETS as a practical, deployable approach for next-generation scalable video delivery.

翻译：大规模视频流媒体事件吸引了数百万同时观看者，给现有传输基础设施带来巨大压力。客户端驱动的自适应机制对共享拥塞反应迟缓，而基于服务器的协调方案则存在可扩展性瓶颈和单点故障风险。本文提出COMETS——一种协同多目标视频传输框架，该框架利用信息中心网络的请求聚合与网络内状态感知等核心原理，实现可扩展、公平且自适应的速率控制。COMETS引入创新的范围兴趣协议与分布式网络内决策流程，在最小化冗余传输的同时，确保接收端组间的视频质量均衡。为此，我们开发了轻量级分布式优化框架，可在无集中控制的情况下指导逐跳质量自适应。大量仿真实验表明，相较于DASH、MoQ及ICN基线方案，COMETS能持续提升带宽利用率、公平性及用户感知体验质量，在高并发场景下表现尤为突出。研究结果凸显了COMETS作为可部署的下一代可扩展视频传输方案的实用价值。