Mystique: A Fine-Grained and Transparent Congestion Control Enforcement Scheme

Mystique: A Fine-Grained and Transparent Congestion Control Enforcement Scheme
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Mystique:细粒度且透明的拥塞控制执行方案

DOI:
10.1109/tnsm.2019.2935829
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发表时间:
2019-08
影响因子:
5.3
通讯作者:
Zhou Jipeng
Zhou Jipeng
中科院分区:
计算机科学2区
文献类型:
--
作者:
Zhang Yuxiang;Cui Lin;Tso Fung Po;Guan Quanlong;Jia Weijia;Zhou Jipeng

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TCP拥塞控制是Web服务延迟的重要组成部分。在实践中,通常使用单一的拥塞控制机制来处理Web服务器上的所有TCP连接,例如默认情况下Linux的Cubic。考虑到复杂多变的网络环境,默认拥塞控制可能并不总是最合适的。调整拥塞控制以满足不同的网络场景通常需要修改服务器上的TCP堆栈。由于生产服务器上的各种操作系统和应用程序配置,这即使不是不可能,也是很困难的。在本文中,我们提出了一个轻量级、灵活和动态的拥塞控制交换方案Mystique,它允许网络或服务器管理员透明地部署任何拥塞控制方案,而无需修改服务器上现有的TCP堆栈。我们已经在Open vSwitch (OVS)中实现了Mystique,并在公共云和私有云环境中进行了广泛的测试实验。实验结果表明,Mystique能够有效地适应各种网络条件,并始终能够对每个TCP连接采用最合适的拥塞控制。更具体地说,与单个拥塞控制相比,Mystique可以显着平均减少18.13%的延迟。
TCP congestion control is a vital component for the latency of Web services. In practice, a single congestion control mechanism is often used to handle all TCP connections on a Web server, e.g., Cubic for Linux by default. Considering complex and ever-changing networking environment, the default congestion control may not always be the most suitable one. Adjusting congestion control to meet different networking scenarios usually requires modification of TCP stacks on a server. This is difficult, if not impossible, due to various operating system and application configurations on production servers. In this paper, we propose Mystique, a light-weight, flexible, and dynamic congestion control switching scheme that allows network or server administrators to deploy any congestion control schemes transparently without modifying existing TCP stacks on servers. We have implemented Mystique in Open vSwitch (OVS) and conducted extensive test-bed experiments in both public and private cloud environments. Experiment results have demonstrated that Mystique is able to effectively adapt to varying network conditions, and can always employ the most suitable congestion control for each TCP connection. More specifically, Mystique can significantly reduce latency by 18.13% on average when compared with individual congestion controls.
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