{"title":"Logical localization of large Internet events","authors":"K. Glass, R. Colbaugh, M. Planck","doi":"10.1109/CCA.2009.5281133","DOIUrl":null,"url":null,"abstract":"The Internet occasionally experiences large disruptions, arising from both natural and manmade disturbances, and it is of significant interest to develop methods for locating within the network the source of a given disruption (i.e., the network element(s) whose perturbation initiated the event). This paper presents a new approach to realizing this logical localization objective. The proposed methodology consists of three steps: 1.) data preprocessing, in which publicly available measurements of Internet activity are acquired, “cleaned”, and assembled into a format suitable for computational analysis, 2.) event characterization via tensor factorization-based time series analysis, and 3.) localization of the source of the disruption through graph theoretic analysis. This procedure provides a principled, automated approach to identifying the root causes of network disruptions at “whole-Internet” scale. The considerable potential of the proposed analytic method is illustrated through both computer simulation studies and empirical.","PeriodicalId":294950,"journal":{"name":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCA.2009.5281133","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
The Internet occasionally experiences large disruptions, arising from both natural and manmade disturbances, and it is of significant interest to develop methods for locating within the network the source of a given disruption (i.e., the network element(s) whose perturbation initiated the event). This paper presents a new approach to realizing this logical localization objective. The proposed methodology consists of three steps: 1.) data preprocessing, in which publicly available measurements of Internet activity are acquired, “cleaned”, and assembled into a format suitable for computational analysis, 2.) event characterization via tensor factorization-based time series analysis, and 3.) localization of the source of the disruption through graph theoretic analysis. This procedure provides a principled, automated approach to identifying the root causes of network disruptions at “whole-Internet” scale. The considerable potential of the proposed analytic method is illustrated through both computer simulation studies and empirical.