Causal analysis of network logs with layered protocols and topology knowledge
Causal analysis of network logs with layered protocols and topology knowledge
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DOI：
10.23919/cnsm46954.2019.9012718
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Satoru Kobayashi;Kazuki Otomo;K. Fukuda
中科院分区：
文献类型：
--
作者：
Satoru Kobayashi;Kazuki Otomo;K. Fukuda
To detect root causes of failures in large-scale networks, we need to extract contextual information from operational data automatically. Correlation-based methods are widely used for this purpose, but they have a problem of spurious correlation, which buries truly important information. In this work, we propose a method for extracting contextual information in network logs by combining a graph-based causal inference algorithm and a pruning method based on domain knowledge (i.e., network protocols and topologies). Applying the proposed method to a set of log data collected from a nation-wide R & E network, we demonstrate that the pruning method reduced processing time by 74% compared with a single-handed causal analysis method, and it detected more useful information for troubleshooting compared with an existing area-based method.
