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基于图团体的告警风暴聚类和定位手段研究.docx

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基于图团体的告警风暴聚类和定位手段研究 Title:ResearchonClusteringandLocalizationofAlarmStormsBasedonGraphCommunity Abstract: Alarmstormsinnetworksrefertosituationswhenalargenumberofalarmsaregeneratedsimultaneously,overwhelmingnetworkoperatorsandmakingitdifficulttoidentifytherootcauseoftheproblem.Toaddressthischallenge,thispaperproposesanovelapproachbasedongraphcommunitytoclusterandlocatealarmstorms.Themethodeffectivelyreducesthecomplexityofalarmstormanalysis,enhancesnetworkmanagementefficiency,andimprovestheoverallnetworkperformance. 1.Introduction Alarmstormsposesignificantchallengesfornetworkmanagementduetothesheervolumeofalarmsgeneratedwithinashortperiod.Traditionalalarmmanagementtechniquesoftenfailtohandlethisproblemeffectively.Therefore,thereisaneedfornewapproachesthatcanidentifyandlocalizealarmstormsaccurately.Thispaperpresentsamethodbasedongraphcommunitytotacklethisissue. 2.LiteratureReview Thissectionreviewsexistingresearchonalarmstorms,graphtheory,clusteringalgorithms,andlocalizationtechniques.Italsohighlightsthelimitationsofcurrentmethodsandsetsthefoundationfortheproposedapproach. 3.Methodology Theproposedmethodconsistsofthreemainsteps:datacollectionandpreprocessing,graphconstruction,andcommunitydetection.Firstly,therawalarmdataiscollectedandpreprocessedtoremovenoiseandredundantinformation.Then,thealarmdataistransformedintoagraphrepresentation,whereeachalarmisrepresentedasanode,andthecorrelationsbetweenalarmsarerepresentedasedges.Finally,graphcommunitydetectionalgorithmsareappliedtoidentifyclustersofalarmsthatformthealarmstorms. 4.ClusteringofAlarmStorms Thecommunitydetectionalgorithms,suchasLouvain,Girvan-Newman,orInfomap,areusedtoidentifyclustersofalarmsthatformalarmstorms.Thesealgorithmsutilizevariousmetrics,suchasmodularityandinformationtheory,tooptimizethedetectionofcommunitieswithinthegraph.Theidentifiedclustersprovideinsightsintotheinterdependentrelationshipsamongalarmsinthestorm. 5.LocalizationofAlarmStorms Oncethealarmstormsareidentified,thenextstepistolocatetheirro