Efficient Job Scheduling in Computational Grid Systems Using Wind Driven Optimization Technique

ComputationalGridhasbeenemployedforsolvingcomplexandlargecomputation-intensiveproblems withthehelpofgeographicallydistributed,heterogeneousanddynamicresources.Jobscheduling isavitalandchallengingfunctionofacomputationalGridsystem.Jobschedulerhastodealwith manyheterogeneouscomputationalresourcesandtotakedecisionsconcerningthedynamic,efficient andeffectiveexecutionofjobs.OptimizationoftheGridperformanceisdirectlyrelatedwiththe efficiencyofschedulingalgorithm.Toevaluatetheefficiencyofaschedulingalgorithm,different parameterscanbeused,themostimportantofwhicharemakespanandflowtime.Inthispaper,a veryrecentevolutionaryheuristicalgorithmknownasWindDrivenOptimization(WDO)isused forefficientlyallocatingjobs toresources inacomputationalGridsystemsothatmakespanand flowtimeareminimized.InordertomeasuretheefficacyofWDO,GeneticAlgorithm(GA)and ParticleSwarmOptimization(PSO)areconsideredforcomparison.ThisstudyprovesthatWDO producesbestresults. KEyWORDS Computational Grid, Flowtime, GA, Job Scheduling, Makespan, PSO, WDO

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