简介：Motivatedbytheprojectsconstrainedbyspacecapacityandresourcetransportingtime,aprojectschedulingproblemwithcapacityconstraintwasmodeled.Ahybridalgorithmisproposed,whichusestheideasofbi-levelschedulingandprojectdecompositiontechnology,andthegeneticalgorithmandtabusearchiscombined.Topologicalreorderingtechnologyisusedtoimprovetheeffciencyofevaluation.Simulationresultsshowtheproposedalgorithmcanobtainsatisfiedschedulingresultsinacceptabletime.

简介：Deadlockmustbeavoidedinamanufacturingsystem.Inthispaper,anefficientalgorithmforfindinganoptimaldeadlock-freeschedulesinamanufacturingsystemwithverylimitedbufferispresented.Thisalgorithmisbasedonheeffectivegeneticalgorithm(GA)searchmethod,andaformalPetrinetstructureisintroducedtodetectthetokenplayerassuringdeadlock-free.InordertomaketheschedulingstrategygeneratedbyGAmeettherequiredconstraintofdeadlock-free,someresultsofthestruetureanalysisofPetrinetareinvolvedasacriteriontoselectdeadlock-freeschedulefromthepopulationgeneratedbyGA.Theeffectivenessandefficiencyoftheproposedapproachisillustratedbyusinganexample.

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简介：ThispaperproposesanobjectorientedmodelschedulingforparallelcomputinginmediaMultiProcessorsSystemonChip(MPSoC).Firstly,theCoarseGrainDataFlowGraph(CGDFG)parallelprogrammingmodelisusedinthisapproach.Secondly,thisapproachhasthefeatureofunifiedabstractionforsoftwareobjectsimplementinginprocessorandhardwareobjectsimplementinginASICs,easyformappingCGDFGprogrammingonMPSoC.Thisapproachcutsdownthekerneloverheadandreducesthecodesizeeffectively.Theprincipleoftheorientedobjectmodel,themethodofscheduling,andhowtomapaparallelprogrammingthroughCGDFGtotheMPSoCareanalyzedinthisapproach.Thisapproachalsocomparesthecodesizeandexecutioncycleswithconventionalcontrolflowscheduling,andpresentsrespectivemanagementoverheadforoneapplicationinme-dia-SoC.

简介：Theplatformschedulingprobleminbattlefieldisoneoftheimportantproblemsinmilitaryoperationalresearch.Itneedstominimizemissioncompletingtimeandmeanwhilemaximizethemissioncompletingaccuracywithalimitednumberofplatforms.Thoughthetraditionalcertainmodelsobtainsomegoodresults,uncertainmodelisstillneededtobeintroducedsincethebattlefieldenvironmentiscomplexandunstable.Anuncertainmodelisprposedfortheplatformschedulingproblem.Relatedparametersinthismodelaresettobefuzzyorstochastic.Duetotheinherentdisadvantageofthesolvingmethodsfortraditionalmodels,anewmethodisproposedtosolvetheuncertainmodel.Finally,thepracticabilityandavailabilityoftheproposedmethodaredemonstratedwithacaseofjointcampaign.

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简介：Howtodealwiththecollaborationbetweentaskdecompositionandtaskschedulingisthekeyproblemoftheintegratedmanufacturingsystemforcomplexproducts.Withthedevelopmentofmanufacturingtechnology,wecanprobeanewwaytosolvethisproblem.Firstly,anewmethodfortaskgranularityquantitativeanalysisisputforward,whichcanpreciselyevaluatethetaskgranularityofcomplexproductcooperationworkflowintheintegratedmanufacturingsystem,ontheabovebasis;thismethodisusedtoguidethecoarse-grainedtaskdecompositionandrecombinethesubtaskswithlowcohesioncoefficient.Then,amulti-objectiveoptimieationmodelandanalgorithmaresetupfortheschedulingoptimizationoftaskscheduling.Finally,theapplicationfeasibilityofthemodelandalgorithmisultimatelyvalidatedthroughanapplicationcasestudy.

简介：Inthispaper,Petrinetstechniqueisintroducedintomobileadhocnetworks(MANET)andapacket-flowparallelschedulingschemeispresentedusingStochasticPetriNets(SPN).Theflowingoftokensisusedingraphicsmodetocharacterizedynamicalfeaturesofsharingasinglewirelesschannel.ThroughSPNreachabilityanalysisandisomorphiccontinuoustimeMarkovprocessequations,somenetworkparameters,suchaschannelefficiencyand,one-hoptransmissiondelay,canbeobtained.ComparedwithThoseofTheconventionalperformanceevaluationmethods,theaboveparametersaremathematicalexpressionsinsteadoftestresultsfromsimulator.

简介：Apowerallocationschemeformulti-usermultiple-inputmultiple-outputorthogonalfrequencydivisionmultiplexing(MIMO-OFDM)systemswithchannelstateinformation(CSI)ontransmitterandreceiverispressed.Multi-userpowerallocationcanbedecoupledintosingleuserpowerallocationthroughoutnullspacemappingofmulti-userchannelandpowerallocationcanbeperformedthroughoutspatial-spectralwater-fillingforperuser.Todealwithmoreusersinsystemandfadingcorrelation,schedulingisperformedtomaintainthegainofpowerallocation.Theproposedschemecansubstantiallyimprovesystem'sspectralefficiencywithlowomplexity.Simulationresultsvalidatetheaccuracyoftheoreticanalyses.

简介：Amemeticalgorithm(MA)foramulti-moderesourceconstrainedprojectschedulingproblem(MRCPSP)isproposed.WeuseanewfitnessfunctionandtwoveryeffectivelocalsearchproceduresintheproposedMA.Thefitnessfunctionmakesuseofamechanismcalled'strategicoscillation'tomakethesearchprocesshaveahigherprobabilitytovisitsolutionsarounda'feasibleboundary'.Oneofthelocalsearchproceduresaimsatimprovingthelowerboundofprojectmakespantobelessthanaknownupperbound,andanotheraimsatimprovingasolutionofanMRCPSPinstanceacceptinginfeasiblesolutionsbasedonthenewfitnessfunctioninthesearchprocess.AdetailedcomputationalexperimentissetupusinginstancesfromtheprobleminstancelibraryPSPLIB.ComputationalresultsshowthattheproposedMAisverycompetitivewiththestate-of-the-artalgorithms.TheMAobtainsimprovedsolutionsforoneinstanceofsetJ30.

简介：Akindofnetworkedcontrolsystemisstudied;thenetworkedcontrolsystemwithnoisedisturbanceismodeledbasedoninformationschedulingandcontrolco-design.Augmentedstatematrixanalysismethodisintroduced,androbustfault-tolerantcontrolproblemofnetworkedcontrolsystemswithnoisedisturbanceunderactuatorfailuresisstudied.Theparametricexpressionofthecontrollerunderactuatorfailuresisgiven.Furthermore,theresultisanalyzedbysimulationtests,whichnotonlysatisfiesthenetworkedcontrolsystemsstability,butalsodecreasesthedatainformationnumberinnetworkchannelandmakesfulluseofthenetworkresources.

简介：Aself-adaptivelargeneighborhoodsearchmethodforschedulingnjobsonmnon-identicalparallelmachineswithmultipletimewindowsispresented.Theproblems'anotherfeatureliesinoversubscription,namelynotalljobscanbescheduledwithinspecifiedschedulinghorizonsduetothelimitedmachinecapacity.Theobjectiveisthustomaximizetheoverallprofitsofprocessedjobswhilerespectingmachineconstraints.Afirst-infirst-outheuristicisappliedtofindaninitialsolution,andthenalargeneighborhoodsearchprocedureisemployedtorelaxandreoptimizecumbersomesolutions.Amachinelearningmechanismisalsointroducedtoconvergeonthemostefficientneighborhoodsfortheproblem.Extensivecomputationalresultsarepresentedbasedondatafromanapplicationinvolvingthedailyobservationschedulingofafleetofearthobservingsatellites.Themethodrapidlysolvesmostprobleminstancestooptimalornearoptimalandshowsarobustperformanceinsensitiveanalysis.

简介：Inordertolowerthepowerconsumptionandimprovethecoefficientofresourceutilizationofcurrentcloudcomputingsystems,thispaperproposestworesourcepre-allocationalgorithmsbasedonthe'shutdowntheredundant,turnonthedemanded'strategyhere.Firstly,agreencloudcomputingmodelispresented,abstractingthetaskschedulingproblemtothevirtualmachinedeploymentissuewiththevirtualizationtechnology.Secondly,thefutureworkloadsofsystemneedtobepredicted:acubicexponentialsmoothingalgorithmbasedontheconservativecontrol(CESCC)strategyisproposed,combiningwiththecurrentstateandresourcedistributionofsystem,inordertocalculatethedemandofresourcesforthenextperiodoftaskrequests.Then,amulti-objectiveconstrainedoptimizationmodelofpowerconsumptionandalow-energyresourceallocationalgorithmbasedonprobabilisticmatching(RA-PM)areproposed.Inordertoreducethepowerconsumptionfurther,theresourceallocationalgorithmbasedontheimprovedsimulatedannealing(RA-ISA)isdesignedwiththeimprovedsimulatedannealingalgorithm.Experimentalresultsshowthatthepredictionandconservativecontrolstrategymakeresourcepre-allocationcatchupwithdemands,andimprovetheefficiencyofreal-timeresponseandthestabilityofthesystem.BothRA-PMandRA-ISAcanactivatefewerhosts,achievebetterloadbalanceamongthesetofhighapplicablehosts,maximizetheutilizationofresources,andgreatlyreducethepowerconsumptionofcloudcomputingsystems.

简介：Thispaperproposesanewqueuingmodelandadaptiveschedulingschemewhichrealizesmulti-classQoSmechanismunderDiffServarchitecture.Thequeuingmodeliscomposedoftwoparalleloutputsubqueues,eachoutputsubqueueadoptsrandomdropalgorithmbysettingdifferentbufferthresholdfordifferentclasstraffic,soitcanprovidemulticlassQoS.Thenewproposedschedulingschemewhichadaptivelychangestheparameterλcanguaranteetheperformancetargetofhighclasstraffic,inthemeantime,improvetheQoSoflowclassestraffic.

简介：Howtoeffectivelyreducetheenergyconsumptionoflarge-scaledatacentersisakeyissueincloudcomputing.Thispaperpresentsanovellow-powertaskschedulingalgorithm(LTSA)forlarge-scaleclouddatacenters.Thewinnertreeisintroducedtomakethedatanodesastheleafnodesofthetreeandthefinalwinneronthepurposeofreducingenergyconsumptionisselected.Thecomplexityoflarge-scaleclouddatacentersisfullyconsider,andthetaskcomparsoncoefficientisdefinedtomaketaskschedulingstrategymorereasonable.Experimentsandperformanceanalysisshowthattheproposedalgorithmcaneffectivelyimprovethenodeutilization,andreducetheoverallpowerconsumptionoftheclouddatacenter.

简介：Inthispaper,anextendedKendallmodelforthepriorityschedulinginput-linegroupoutputwithmulti-channelinAsynchronousTransferMode(ATM)exchangesystemisproposedandthenthemeanmethodisusedtomodelmathematicallythenon-typicalnon-anticipativePRiorityservice(PR)model.Comparedwiththetypicalandnon-anticipativePRmodel,itexpressesthecharacteristicsofthepriorityschedulinginput-linegroupoutputwithmulti-channelinATMexchangesystem.ThesimulationexperimentshowsthatthismodelcanimprovetheHOLblockandtheperfonnanceofinput-queuedATMswitchnetworkdramatically.ThismodelhasabetterdevelopingprospectinATMexchangesystem.

简介：Amodifiedbottleneck-based(MB)heuristicforlarge-scalejob-shopschedulingproblemswithawell-definedbottleneckissuggested,whichissimplerbutmoretailoredthantheshiftingbottleneck(SB)procedure.Inthisalgorithm,thebottleneckisfirstscheduledoptimallywhilethenon-bottleneckmachinesaresubordinatedaroundthesolutionsofthebottleneckschedulebysomeeffectivedispatchingrules.ComputationalresultsindicatethattheMBheuristiccanachieveabettertradeoffbetweensolutionqualityandcomputationaltimecomparedtoSBprocedureformedium-sizeproblems.Furthermore,itcanobtainagoodsolutioninashorttimeforlarge-scalejob-shopschedulingproblems.