A commonly held belief is that traffic engineering and routing changes are infrequent. However, based on our measurements over a number of years of traffic between data centers in one of the largest cloud provider's networks, we found that it is common for flows to change paths at ten-second intervals or even faster. These frequent path and, consequently, latency variations can negatively impact the performance of cloud applications, specifically, latency-sensitive and geo-distributed applications. Our recent measurements and analysis focused on observing path changes and latency variations between different Amazon aws regions. To this end, we devised a path change detector that we validated using both ad hoc experiments and feedback from cloud networking experts. The results provide three main insights: (1) Traffic Engineering (TE) frequently moves (TCP and UDP) flows among network paths of different latency, (2) Flows experience unfair performance, where a subset of flows between two machines can suffer large latency penalties (up to 32% at the 95th percentile) or excessive number of latency changes, and (3) Tenants may have incentives to selfishly move traffic to low latency classes (to boost the performance of their applications). We showcase this third insight with an example using rsync synchronization. To the best of our knowledge, this is the first paper to reveal the high frequency of TE activity within a large cloud provider's network. Based on these observations, we expect our paper to spur discussions and future research on how cloud providers and their tenants can ultimately reconcile their independent and possibly conflicting objectives. Our data is publicly available for reproducibility and further analysis at http://goo.gl/25BKte.

中文翻译：

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云中的路径持久性

一个普遍持有的信念是流量工程和路由更改很少发生。然而，根据我们多年来对最大云提供商网络之一中数据中心之间流量的测量，我们发现流以 10 秒甚至更快的间隔更改路径是很常见的。这些频繁的路径以及因此的延迟变化可能会对云应用程序的性能产生负面影响，特别是延迟敏感和地理分布的应用程序。我们最近的测量和分析侧重于观察不同 Amazon aws 区域之间的路径变化和延迟变化。为此，我们设计了一个路径变化检测器，我们使用临时实验和云网络专家的反馈对其进行了验证。结果提供了三个主要见解：(1) 流量工程 (TE) 经常在不同延迟的网络路径之间移动（TCP 和 UDP）流，(2) 流会遇到不公平的性能，其中两台机器之间的流子集可能会遭受很大的延迟惩罚（在95%）或过多的延迟变化，以及（3）租户可能有动机自私地将流量转移到低延迟类别（以提高其应用程序的性能）。我们通过使用 rsync 同步的示例来展示这第三个见解。据我们所知，这是第一篇揭示大型云提供商网络中 TE 活动的高频率的论文。基于这些观察，我们希望我们的论文能够激发关于云提供商及其租户如何最终协调其独立且可能相互冲突的目标的讨论和未来研究。我们的数据可在 http://goo.gl/25BKte 上公开获得，以进行可重复性和进一步分析。