Fault Localization in Cloud using Centrality Measures

R. NarayanaaS, M. Sivaranjan, S. LekshmiR
{"title":"Fault Localization in Cloud using Centrality Measures","authors":"R. NarayanaaS, M. Sivaranjan, S. LekshmiR","doi":"10.1109/STC55697.2022.00033","DOIUrl":null,"url":null,"abstract":"Fault localization is an imperative method in fault tolerance in a distributed environment that designs a blueprint for continuing the ongoing process even when one or many modules are non-functional. Visualizing a distributed environment as a graph, whose nodes represent faults (fault graph), allows us to introduce probabilistic weights to both edges and nodes that cause the faults. With multiple modules like databases, run-time cloud, etc. making up a distributed environment and extensively, a cloud environment, we aim to address the problem of optimally and accurately performing fault localization in a distributed environment by modifying the Graph optimization approach to localization and centrality, specific to fault graphs.","PeriodicalId":170123,"journal":{"name":"2022 IEEE 29th Annual Software Technology Conference (STC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 29th Annual Software Technology Conference (STC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STC55697.2022.00033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Fault localization is an imperative method in fault tolerance in a distributed environment that designs a blueprint for continuing the ongoing process even when one or many modules are non-functional. Visualizing a distributed environment as a graph, whose nodes represent faults (fault graph), allows us to introduce probabilistic weights to both edges and nodes that cause the faults. With multiple modules like databases, run-time cloud, etc. making up a distributed environment and extensively, a cloud environment, we aim to address the problem of optimally and accurately performing fault localization in a distributed environment by modifying the Graph optimization approach to localization and centrality, specific to fault graphs.
基于中心性度量的云故障定位
故障定位是分布式环境容错中的一种必要方法,分布式环境可以设计蓝图,以便在一个或多个模块失效时继续执行正在进行的流程。将分布式环境可视化为一个图,其节点表示故障(故障图),允许我们向导致故障的边和节点引入概率权重。数据库、运行时云等多个模块组成了一个分布式环境和一个广泛的云环境,我们的目标是通过修改图优化方法来定位和中心性,具体到故障图,解决在分布式环境中最优、准确地执行故障定位的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信