论文标题

P4代码:可编程数据平面硬件的体验

P4-CoDel: Experiences on Programmable Data Plane Hardware

论文作者

Kundel, Ralf, Rizk, Amr, Blendin, Jeremias, Koldehofe, Boris, Hark, Rhaban, Steinmetz, Ralf

论文摘要

固定的计算机网络中的缓冲尺寸,尤其是Internet,是延迟和带宽之间的折衷。一项支持高带宽的决定,暗示更大的缓冲区,因此由于不断填充的缓冲液而下属延迟。这种现象称为Bufferbloat。主动队列管理(AQM)算法(例如CODEL或PIE),旨在在基于软件的主机上使用,通过控制队列填充,从而通过微妙的数据包下降来提供流动不可知的补救措施,从而为延迟填充。在以前的工作中,我们已经证明了数据平面编程语言P4足够强大,可以实现CODEL算法。尽管可以轻松地将旧软件算法汇编为几乎所有处理体系结构,但对于可编程数据平面硬件(即可编程数据包处理器)上的AQM而言,这通常是不正确的。在这项工作中,我们重点介绍了相应的挑战,演示了如何应对它们,并提供了能够在不同的高速P4可编程数据平面硬件硬件目标上实现此类AQM算法的技术。此外,我们还提供了在不同的P4可编程数据平面目标上创建的测量结果。所得的延迟测量结果揭示了在这些设备内执行主动队列管理的可行性和约束。最后,我们发布了源代码和说明,以重现本文作为研究社区的开源。

Fixed buffer sizing in computer networks, especially the Internet, is a compromise between latency and bandwidth. A decision in favor of high bandwidth, implying larger buffers, subordinates the latency as a consequence of constantly filled buffers. This phenomenon is called Bufferbloat. Active Queue Management (AQM) algorithms such as CoDel or PIE, designed for the use on software based hosts, offer a flow agnostic remedy to Bufferbloat by controlling the queue filling and hence the latency through subtle packet drops. In previous work, we have shown that the data plane programming language P4 is powerful enough to implement the CoDel algorithm. While legacy software algorithms can be easily compiled onto almost any processing architecture, this is not generally true for AQM on programmable data plane hardware, i.e., programmable packet processors. In this work, we highlight corresponding challenges, demonstrate how to tackle them, and provide techniques enabling the implementation of such AQM algorithms on different high speed P4-programmable data plane hardware targets. In addition, we provide measurement results created on different P4-programmable data plane targets. The resulting latency measurements reveal the feasibility and the constraints to be considered to perform Active Queue Management within these devices. Finally, we release the source code and instructions to reproduce the results in this paper as open source to the research community.

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