StreamGuard通过分流级优先级调度，显著提升5G视频会议体验与公平性。
StreamGuard: Exploring a 5G Architecture for Efficient, Quality of Experience-Aware Video Conferencing
- 基于网络侧深度包检测，实现会话内子流的体验感知优先级控制
- 实测在同等背景吞吐下体验提升最高70%，或保持两倍背景吞吐
- 适合需要高实时性与资源公平性的5G视频会议系统部署
5G视频会议应用日益普及，但在无线资源受限时用户体验（QoE）常下降。原因在于5G需服务大量用户，且交互式流量需精细处理。我们提出并实现了一种名为StreamGuard的实用5G架构，支持子流级别的、面向体验的优先级调度。该系统形成闭环控制：在接入网（RAN）中部署监控模块，通过深度包检测推断QoE和网络状态；控制器据此选择优先级策略，在体验与公平间取得平衡；标记模块则通过打标将数据包引导至相应优先队列。此外，通过选择性丢弃子流和基于探测的速率控制机制，主动调整应用行为以适配无线约束。在真实5G测试床上的实验表明，相较原生5G及现有最优方案，StreamGuard实现了更优的体验-公平性权衡：在相近背景吞吐下，体验最高提升70%；或在相似体验水平下，背景吞吐保持高达2倍。
原文摘要 · Abstract (English)
Video conferencing over 5G is increasingly prevalent, yet its Quality of Experience (QoE) often degrades under limited radio resources. This has two causes: 5G networks must serve many users, while interactive traffic requires careful handling. Motivated by the insight that different subflows within an interactive session have a disproportionate effect on QoE, we present the design and implementation of StreamGuard, a practical 5G architecture for subflow-level, QoE-aware prioritization. StreamGuard forms a closed control loop with three components: (1) a monitor in the Radio Access Network (RAN) that uses deep packet inspection to infer QoE and RAN state, (2) a controller that selects prioritization actions to balance QoE and fairness, and (3) a marking module that applies these decisions by marking packets to steer subflows into appropriate priority queues. StreamGuard further shapes application behaviors via mechanisms including selective subflow dropping and probe-based rate control, to align application behavior with radio constraints. Implemented in a real 5G testbed, StreamGuard achieves a superior QoE-fairness tradeoff compared to vanilla 5G and prior state-of-the-art approaches, improving QoE by up to 70% at comparable background throughput or preserving up to 2x higher background throughput at similar QoE.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。