The value of repeatable experiments and negative results: - a journey through the history and future of AQM and fair queuing algorithms.

Dave Täht
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引用次数: 1

Abstract

The Bufferbloat project was founded three and half years ago to explore solutions to why modern data networks became so slow when loaded. We set out to explore the literature, and code, from the earliest days of the Internet to today, to try and find out what had gone wrong, and to find ways to fix it. A result of that effort (so far!) has been a renaissance in interest in congestion control, and huge - orders of magnitude - improvements in network latency along the edge of the Internet, with deployable new algorithms and code. Surprisingly, we also made large improvements in simultaneous bidirectional goodput on asymmetric networks. This talk goes into the history and future of Active Queue Management (AQM) and fair queuing algorithms, touches upon current work across the field and tries to identify useful techniques for exploring and designing future work that can scale.
可重复实验和负面结果的价值:-回顾AQM和公平排队算法的历史和未来。
Bufferbloat项目成立于三年半前,旨在探索现代数据网络在加载时变得如此缓慢的解决方案。我们开始探索从互联网早期到今天的文献和代码,试图找出哪里出了问题,并找到解决问题的方法。这些努力(到目前为止!)的结果是对拥塞控制的兴趣复兴,以及互联网边缘的网络延迟的巨大数量级的改进,以及可部署的新算法和代码。令人惊讶的是,我们在非对称网络上的同时双向发送方面也取得了很大的进步。本次演讲将探讨主动队列管理(AQM)和公平排队算法的历史和未来,触及该领域的当前工作,并试图确定探索和设计可扩展的未来工作的有用技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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