FlashPass:浅缓冲广域网的主动拥塞控制

Gaoxiong Zeng, J. Qiu, Yifei Yuan, H. Liu, Kai Chen
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引用次数: 8

摘要

近年来,大型企业(如谷歌、阿里巴巴等)一直在构建和部署基于浅缓冲交换芯片的广域路由器。然而,使用传统的响应式传输(例如,TCP Cubic),浅缓冲区很容易被大型BDP广域流量淹没,导致高数据包丢失和吞吐量降低。为了解决这个问题,我们问:我们能否设计一种传输方式,同时实现浅缓冲广域网的高吞吐量和低损耗?我们通过采用主动拥塞控制(PCC)肯定地回答了这个问题。然而,现有PCC要在WAN上工作存在两个问题。首先,广域流量具有不同的rtt,导致我们所说的不完美调度问题(例如,数据及时崩溃)。其次,信用触发数据发送有一个RTT延迟,这可能会降低网络性能。因此,我们提出了一种新颖的PCC设计——FlashPass。为了解决第一个问题,FlashPass采用了发送端驱动的仿真过程,并进行了发送时间校准,以避免数据包崩溃。为了解决第二个问题,FLASHPASS允许在开始阶段进行早期数据传输,并在结束阶段采用选择性丢弃机制进行过度配置,以实现有效的信用分配。我们对生产负荷的评估表明,FlashPass将TCP Cubic和ExpressPass的总流量完井时间分别缩短了32%和11.4%,将小流量的第99尾完井时间分别缩短了49.5%和38%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FlashPass: Proactive Congestion Control for Shallow-buffered WAN
In recent years, large enterprises (e.g., Google, Alibaba, etc.) have been building and deploying their wide-area routers based on shallow-buffered switching chips. However, with legacy reactive transport (e.g., TCP Cubic), shallow buffer can easily get overwhelmed by large BDP wide-area traffic, leading to high packet losses and degraded throughput. To address it, we ask: can we design a transport to simultaneously achieve high throughput and low loss for shallow-buffered WAN?We answer this question affirmatively by employing proactive congestion control (PCC). However, two issues exist for existing PCC to work on WAN. Firstly, wide-area traffics have diverse RTTs, leading to what we called imperfect scheduling issue (e.g., data crash in time). Secondly, there is one RTT delay for credits to trigger data sending, which may degrade network performance. Therefore, we propose a novel PCC design - FlashPass. To address the first issue, FlashPass adopts sender-driven emulation process with send time calibration to avoid the data packet crash. To address the second issue, FLASHPASS enables early data transmission in the starting phase, and incorporates an over-provisioning with selective dropping mechanism for efficient credit allocation in the finishing phase. Our evaluation with production workload demonstrates that FlashPass reduces the overall flow completion times of TCP Cubic and ExpressPass by up to 32% and 11.4%, and the 99-th tail completion times of small flows by up to 49.5% and 38%, respectively.
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