论文标题

双队列耦合AQM:所有人的可部署非常低的排队延迟

Dual Queue Coupled AQM: Deployable Very Low Queuing Delay for All

论文作者

De Schepper, Koen, Albisser, Olga, Tilmans, Olivier, Briscoe, Bob

论文摘要

在互联网上,传统上认为亚毫秒的排队延迟和寻求能力的人被认为是相互排斥的。我们引入了一项提供的服务:低延迟损失可伸缩吞吐量(L4S)。当在使用真实住宅宽带设备上模拟在测试床上进行测试时,队列延迟保持低(中位100--300 $ $ $ s)和一致(即使在高度动态的工作负载下,低于2 ms),而没有损害其他指标(零很多量损失和接近充分利用)。 L4S利用“可伸缩”拥塞控制的性能(例如DCTCP,TCP Prague)。但是,使用这种拥塞控制的流动非常激进,这会引起部署挑战,因为L4S必须与所谓的“经典”流(例如Reno,Cubic)共存。本文介绍了一个架构解决方案:“双队列耦合的活动队列管理”,该解决方案可以在可扩展和经典流之间平衡。它可以抵消可扩展流的更具侵略性的反应,而无需检查流动标识符。双队列结构已作为Linux排队纪律实现。它的作用像半渗透的膜,隔离了可扩展和“经典”流量的延迟,但将其容量耦合到一个带宽池中。本文证明了设计和实施选择合理的合理性,并可视化数十万实验的代表性选择以测试我们的主张。

On the Internet, sub-millisecond queueing delay and capacity-seeking have traditionally been considered mutually exclusive. We introduce a service that offers both: Low Latency Low Loss Scalable throughput (L4S). When tested under a wide range of conditions emulated on a testbed using real residential broadband equipment, queue delay remained both low (median 100--300 $μ$s) and consistent (99th percentile below 2 ms even under highly dynamic workloads), without compromising other metrics (zero congestion loss and close to full utilization). L4S exploits the properties of `Scalable' congestion controls (e.g., DCTCP, TCP Prague). Flows using such congestion control are however very aggressive, which causes a deployment challenge as L4S has to coexist with so-called `Classic' flows (e.g., Reno, CUBIC). This paper introduces an architectural solution: `Dual Queue Coupled Active Queue Management', which enables balance between Scalable and Classic flows. It counterbalances the more aggressive response of Scalable flows with more aggressive marking, without having to inspect flow identifiers. The Dual Queue structure has been implemented as a Linux queuing discipline. It acts like a semi-permeable membrane, isolating the latency of Scalable and `Classic' traffic, but coupling their capacity into a single bandwidth pool. This paper justifies the design and implementation choices, and visualizes a representative selection of hundreds of thousands of experiment runs to test our claims.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源