摘要
Streamprocessingapplicationscontinuouslyprocesslargeamountsofonlinestreamingdatainrealtimeornearrealtime.Theyhavestrictlatencyconstraints.However,thecontinuousprocessingmakesthemvulnerabletoanyfailures,andtherecoveriesmayslowdowntheentireprocessingpipelineandbreaklatencyconstraints.Theupstreambackupschemeisoneofthemostwidelyappliedfault-tolerantschemesforstreamprocessingsystems.Itintroducescomplexbackupdependenciestotasks,whichincreasesthedifficultyofcontrollingrecoverylatencies.Moreover,whendependenttasksarelocatedonthesameprocessor,theyfailatthesametimeinprocessor-levelfailures,bringingextrarecoverylatenciesthatincreasetheimpactsoffailures.Thispaperstudiestherelationshipbetweenthetaskallocationandtherecoverylatencyofastreamprocessingapplication.Wepresentacorrelatedfailureeffectmodeltodescribetherecoverylatencyofastreamtopologyinprocessor-levelfailuresunderataskallocationplan.Weintroducearecovery-latencyawaretaskallocationproblem(RTAP)thatseekstaskallocationplansforstreamtopologiesthatwillachieveguaranteedrecoverylatencies.WediscussthedifferencebetweenRTAPandclassictaskallocationproblemsandpresentaheuristicalgorithmwithacomputationalcomplexityofO(nlog2n)tosolvetheproblem.Extensiveexperimentswereconductedtoverifythecorrectnessandeffectivenessofourapproach.Itimprovestheresourceusageby15%-20%onaverage.
出版日期
2018年06月16日(中国期刊网平台首次上网日期,不代表论文的发表时间)