论文标题
使用被动分析（海报摘要和海报）的Internet停电检测
Internet Outage Detection using Passive Analysis (Poster Abstract and Poster)
论文作者
论文摘要
自然灾害，政治事件，软件或硬件问题的中断以及人为错误在电子商务上付出了巨大的费用（在亚马逊每分钟\ $ $ $ 66K）。虽然几个现有系统检测到Internet停电，但这些系统通常太僵化了，整个Internet上具有固定参数，具有类似Cusum的变化检测。相反，我们建议使用被动数据的系统，以涵盖IPv4和IPv6，为每个块自定义参数，以优化我们的贝叶斯推理模型的性能。我们的海报描述了我们的三个贡献：首先，我们显示自定义参数如何允许我们通常检测出良好的时间尺度（5分钟）和精细空间分辨率（ /24 IPv4和 /48 IPv6块）的中断。我们的第二个贡献是表明，通过对不同块的调整参数不同，我们可以缩小时间精度以涵盖更具挑战性的块。最后，我们显示我们的方法扩展到IPv6，并提供了IPv6中断的第一个报告。
Outages from natural disasters, political events, software or hardware issues, and human error place a huge cost on e-commerce (\$66k per minute at Amazon). While several existing systems detect Internet outages, these systems are often too inflexible, with fixed parameters across the whole internet with CUSUM-like change detection. We instead propose a system using passive data, to cover both IPv4 and IPv6, customizing parameters for each block to optimize the performance of our Bayesian inference model. Our poster describes our three contributions: First, we show how customizing parameters allows us often to detect outages that are at both fine timescales (5 minutes) and fine spatial resolutions (/24 IPv4 and /48 IPv6 blocks). Our second contribution is to show that, by tuning parameters differently for different blocks, we can scale back temporal precision to cover more challenging blocks. Finally, we show our approach extends to IPv6 and provides the first reports of IPv6 outages.
