{"title":"基于大数据的网络故障快速定位方法研究","authors":"Jun-Wei Huang, B. Jin, H. Meng, Dongling Xiao","doi":"10.1109/IWECAI50956.2020.00024","DOIUrl":null,"url":null,"abstract":"The stable and reliable operation of the power grid information system is the fundamental to ensure the safe production and optimal management of the power grid. In this paper, by obtaining the performance parameters of the system between load and response time, resource consumption, and introducing time, external time and other parameters for big data analysis, the performance trend analysis of throughput, error and response time is given, and the current situation and history of the system are analyzed Historical data comparison and performance bottleneck analysis can improve the level of information mining, quickly and accurately realize the location of network fault components and fault type and cause identification","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Fast Location Method of Network Fault Based on Big Data\",\"authors\":\"Jun-Wei Huang, B. Jin, H. Meng, Dongling Xiao\",\"doi\":\"10.1109/IWECAI50956.2020.00024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The stable and reliable operation of the power grid information system is the fundamental to ensure the safe production and optimal management of the power grid. In this paper, by obtaining the performance parameters of the system between load and response time, resource consumption, and introducing time, external time and other parameters for big data analysis, the performance trend analysis of throughput, error and response time is given, and the current situation and history of the system are analyzed Historical data comparison and performance bottleneck analysis can improve the level of information mining, quickly and accurately realize the location of network fault components and fault type and cause identification\",\"PeriodicalId\":364789,\"journal\":{\"name\":\"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWECAI50956.2020.00024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWECAI50956.2020.00024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Fast Location Method of Network Fault Based on Big Data
The stable and reliable operation of the power grid information system is the fundamental to ensure the safe production and optimal management of the power grid. In this paper, by obtaining the performance parameters of the system between load and response time, resource consumption, and introducing time, external time and other parameters for big data analysis, the performance trend analysis of throughput, error and response time is given, and the current situation and history of the system are analyzed Historical data comparison and performance bottleneck analysis can improve the level of information mining, quickly and accurately realize the location of network fault components and fault type and cause identification