首页> 外文期刊>NTT Technical Review >Network Failure Detection and Diagnosis by Analyzing Syslog and SNS Data: Applying Big Data Analysis to Network Operations
【24h】

Network Failure Detection and Diagnosis by Analyzing Syslog and SNS Data: Applying Big Data Analysis to Network Operations

机译:通过分析Syslog和SNS数据进行网络故障检测和诊断:将大数据分析应用于网络运营

获取原文
           

摘要

We introduce two big data analysis methods for diagnosing the causes of network failures and for detecting network failures early. Syslogs contain log data generated by the system. We analyzed syslogs and succeeded in detecting the cause of a network failure by automatically learning over 100 million logs without needing any previous knowledge of log data. Analysis of the data of a social networking service (namely, Twitter) enabled us to detect possible network failures by extracting network-failure related tweets, which account for less than 1% of all tweets, in real time and with high accuracy.
机译:我们介绍了两种大数据分析方法,用于诊断网络故障的原因和及早发现网络故障。 Syslog包含系统生成的日志数据。我们分析了系统日志,并通过自动学习超过1亿条日志,而无需任何先前的日志数据知识,成功地检测出网络故障的原因。对社交网络服务(即Twitter)数据的分析使我们能够通过实时且高精度地提取与网络故障相关的推文来检测可能的网络故障,这些推文占所有推文的不到1%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号