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Failure cause identification system, failure cause identification method and failure cause identification program

机译:故障原因识别系统,故障原因识别方法和故障原因识别程序

摘要

PROBLEM TO BE SOLVED: To improve the efficiency of operation of an ICT infrastructure by shortening the time required to identify the cause of a failure. SOLUTION: A failure cause identification system 150 causes an abnormality in an application from the configuration information of a network system 100 based on a first concept (“when a plurality of abnormalities occur at the same time, a common factor exists”). Extract the related nodes that are related to the new node. Each metric of the extracted related node is set as an "objective variable", and the others are candidates for "explanatory variable", and an explanatory variable that can be used as a prediction model for each objective variable is selected from the candidates. An abnormality of the objective variable is detected by JIT determination, and the objective variable for which the abnormality is detected and its explanatory variable are detected. Next, based on the second idea (“If there is a factor common to multiple anomalies, it is highly likely that it is the cause of the anomaly”), the objective common to each explanatory variable of the objective variable in which the anomaly is detected. The number of variables is extracted, and the one with the largest number is the first candidate for the cause of abnormality. [Selection diagram] Fig. 1
机译:要解决的问题:通过缩短识别失败原因所需的时间来提高ICT基础设施的运行效率。解决方案:故障原因识别系统150基于第一概念(“当多个异常同时发生时,存在共同因子”),原因识别系统150在网络系统100的配置信息中引起异常。提取与新节点相关的相关节点。提取相关节点的每个度量标准被设置为“物镜变量”,而其他度量是“解释变量”的候选者,并且可以从候选者中选择可以用作每个物体变量的预测模型的解释变量。通过JIT确定检测目标变量的异常,检测到异常的物镜变量及其解释变量。接下来,基于第二种想法(“如果有多个异常常见的因子,则很可能是异常的原因”),对异常的目标变量的每个解释性变量的常见的目标是检测到。提取的变量数量,数量最大的数量是异常原因的第一个候选者。 [选择图]图1

著录项

  • 公开/公告号JP2021149849A

    专利类型

  • 公开/公告日2021-09-27

    原文格式PDF

  • 申请/专利权人 富士通株式会社;

    申请/专利号JP20200051630

  • 发明设计人 藤田 裕志;渡辺 幸洋;

    申请日2020-03-23

  • 分类号G06F11/07;

  • 国家 JP

  • 入库时间 2022-08-24 21:16:41

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