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.
