Modeling the Performance of MapReduce Applications for the Cloud

Iván Carrera, Claudio Geyer
2015 Latin American Journal of Computing  
In thelastyears,CloudComputinghasbecomea keytechnologythatmadepossibletorunapplicationswithout needing todeployaphysicalinfrastructure.Thechallengewith deploying distributedapplicationsinCloudComputingenvi- ronmentsisthatthevirtualmachineinfrastructureshouldbe planned inatimeandcost-effectiveway. This workisasummaryofapreviousworkpresentedbythe authors asaMaster'sthesis,withthegoalofshowingthatthe execution timeofadistributedMapReduceapplication,running in
more » ... edusinga 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.
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