When many users and unique applications share a congested edge link (e.g., a home network), everyone wants their own application to continue to perform well despite contention over network resources. Traditionally, network engineers have focused on fairness as the key objective to ensure that competing applications are equitably and led by the switch, and hence have deployed fair queueing mechanisms. However, for many network workloads today, strict fairness is directly at odds with equitable application performance. Real-time streaming applications, such as videoconferencing, suffer the most when network performance is volatile (with delay spikes or sudden and dramatic drops in throughput). Unfortunately, "fair" queueing mechanisms lead to extremely volatile network behavior in the presence of bursty and multi-flow applications such as Web traffic. When a sudden burst of new data arrives, fair queueing algorithms rapidly shift resources away from incumbent flows, leading to severe stalls in real-time applications. In this paper, we present Confucius, the first practical queue management scheme to effectively balance fairness against volatility, providing performance outcomes that benefit all applications sharing the contended link. Confucius outperforms realistic queueing schemes by protecting the real-time streaming flows from stalls in competing with more than 95% of websites. Importantly, Confucius does not assume the collaboration of end-hosts, nor does it require manual parameter tuning to achieve good performance.

翻译：当众多用户和独特应用共享一条拥塞的边缘链路（例如家庭网络）时，尽管网络资源存在争用，每个人都希望自己的应用能够持续良好运行。传统上，网络工程师将公平性作为关键目标，以确保竞争性应用由交换机主导实现公平分配，因此部署了公平排队机制。然而，对于当今许多网络工作负载而言，严格公平性与均衡的应用性能直接矛盾。实时流媒体应用（如视频会议）在网络性能波动（出现延迟尖峰或吞吐量突然急剧下降）时受损最为严重。遗憾的是，“公平”排队机制在面对突发性和多流应用（如Web流量）时，会导致极其波动的网络行为。当新数据突发到达时，公平排队算法会迅速将资源从现有流中转移，导致实时应用出现严重停顿。在本文中，我们提出Confucius，这是首个能有效平衡公平性与波动性的实用队列管理方案，可为共享争用链路的所有应用带来性能收益。Confucius通过保护实时流媒体流在与超过95%的网站竞争时免受停顿，优于现实排队方案。重要的是，Confucius不假设端主机的协作，也无需手动参数调优即可实现良好性能。