Latin-American Journal of Computing (Nov 2015)
Modeling the Performance of MapReduce Applications for the Cloud
Abstract
In thelastyears,CloudComputinghasbecomea keytechnologythatmadepossibletorunapplicationswithout needing todeployaphysicalinfrastructure.Thechallengewith deploying distributedapplicationsinCloudComputingenvi- ronmentsisthatthevirtualmachineinfrastructureshouldbe planned inatimeandcost-effectiveway. This workisasummaryofapreviousworkpresentedbythe authors asaMaster’sthesis,withthegoalofshowingthatthe execution timeofadistributedMapReduceapplication,running in aCloudcomputingenvironment,canbepredictedusinga mathematical modelbasedontheoreticalspecifications.This predictionismadetohelptheusersoftheCloudComputing environmenttoplantheirdeployments,i.e.,quantifythenumber of virtualmachinesanditscharacteristics.Aftermeasuringthe application executiontimeandvaryingparametersstatedinthe mathematical model,andafterthat,usingalinearregression technique, thegoalisachievedfindingamodeloftheexecution time whichwasthenappliedtopredicttheexecutiontimeof MapReduce applications.Experimentswereconductedinseveral configurations andshowedaclearrelationwiththetheoretical model, revealingthatthemodelisinfactabletopredictthe execution timeofMapReduceapplications.Thedevelopedmodel is generic,meaningthatitusestheoreticalabstractionsforthe computing capacityoftheenvironmentandthecomputingcost of theMapReduceapplication.