简介:Howtodealwiththecollaborationbetweentaskdecompositionandtaskschedulingisthekeyproblemoftheintegratedmanufacturingsystemforcomplexproducts.Withthedevelopmentofmanufacturingtechnology,wecanprobeanewwaytosolvethisproblem.Firstly,anewmethodfortaskgranularityquantitativeanalysisisputforward,whichcanpreciselyevaluatethetaskgranularityofcomplexproductcooperationworkflowintheintegratedmanufacturingsystem,ontheabovebasis;thismethodisusedtoguidethecoarse-grainedtaskdecompositionandrecombinethesubtaskswithlowcohesioncoefficient.Then,amulti-objectiveoptimieationmodelandanalgorithmaresetupfortheschedulingoptimizationoftaskscheduling.Finally,theapplicationfeasibilityofthemodelandalgorithmisultimatelyvalidatedthroughanapplicationcasestudy.
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简介:Sinceearlythisyear,thesituationinAfghanistanhasbeenturbulentwithoperationsoftheTalibanbecomingmoreactive
简介:Duringrecentyears,somenotionsabouttaskshavebeenconsideredasthemajorpartofanalysisindifferentteachingapproachesandteachersarebeingmoreinterestedintheuseoftaskbasedapproachbothinforeignandinsecondlanguageteaching.Themaingoalofthisarticleistointroduceanddiscusssomemajorprinciplesoftask-basedlanguageteachingandindicateshowteacherscanapplythemintheircurriculum.
简介:异构的计算(HC)环境与不同计算能力利用多样的资源解决有多样的计算要求和限制的计算集中的应用程序。在HC环境的任务指派问题能正式至于任务和机器的一个给定的集合被定义,把最小使平底锅成为的任务分到完成的机器。在这篇论文,我们建议首先安排启发式的、高标准偏差的一项新任务(HSTDF),它把一项任务的期望的实行时间的标准偏差看作一个选择标准。一项任务的期望的实行时间的标准偏差在不同机器上在任务实行时间代表变异量。我们的结论是有高标准偏差的任务必须为安排被分配第一。实验的一个大数被执行检查有效性求婚在有存在启发规则的不同情形,和比较启发式(Max-min,Sufferage,分割了Min平均的、分割的Min-min,并且分割了Max-min)清楚地表明求婚启发式以一般水准超过所有存在启发规则做平底锅。
简介:而其中的中心任务(Main Task)则体现了这一单元的最终成果,中心任务作为一个单元的高潮部分,中心任务(Main Task)和检测(Checkout)
简介: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.