路径拼接:基于现有测量的全互联网路径和延迟估计

D. K. Lee, K. Jang, Changhyun Lee, G. Iannaccone, S. Moon
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引用次数: 10

摘要

近年来提出了许多测量系统来阐明互联网的内部性能。它们的共同目标是允许分布式应用程序改善最终用户体验。他们面临的一个常见障碍是需要部署另一个度量基础设施。在这项工作中,我们证明了在没有任何新的测量基础设施或主动探测的情况下,我们可以从as - as段获得复合性能估计,并且估计与使用按需定制的主动探测的现有估计方法一样好(甚至更好)。本文的主要贡献是一种估计算法,该算法将测量数据分解成片段,有效地识别相关片段,并通过仔细地将片段拼接在一起,产生任意两个端点之间的延迟和路径估计。恰当地说,我们称之为路径拼接算法。我们的结果显示出非常好的准确性:在80%的端到端路径中延迟误差低于20 ms。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path Stitching: Internet-Wide Path and Delay Estimation from Existing Measurements
Many measurement systems have been proposed in recent years to shed light on the internal performance of the Internet. Their common goal is to allow distributed applications to improve end-user experience. A common hurdle they face is the need to deploy yet another measurement infrastructure. In this work, we demonstrate that without any new measurement infrastructure or active probing we obtain composite performance estimates from AS-by-AS segments and the estimates are as good as (or even better than) those from existing estimation methodologies that use on-demand, customized active probing. The main contribution of this paper is an estimation algorithm that breaks down measurement data into segments, identifies relevant segments efficiently, and, by carefully stitching segments together, produces delay and path estimates between any two end points. Fittingly, we call our algorithm path stitching. Our results show remarkably good accuracy: error in delay is below 20 ms in 80% of end-to-end paths.
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