Khadraoui, Khouloud Melazem, Rym2023-07-032023-07-032023-06-07https://dspace.univ-eloued.dz/handle/123456789/27449mémoire mastre informatuqueFogComputingcomplementsCloudComputinginmeetingthespecificrequirementsofthe IoT.ItenableslocaldataprocessingnearIoTdevices,reducinglatencyandimprovingreal-time responsiveness.However,managingscalabilityinaFogenvironmentcanbeachallenge.Infras- tructure managementandorchestrationtoolsplayacrucialroleinaddressingthischallengeby ensuring seamlessdeployment,monitoring,andscalabilityofservicesinaFoginfrastructure. In thiswork,Weproposedanauto-scalingalgorithmspecificallydesignedforFogCom- puting infrastructurethatutilizeacontainerizedarchitectureandorchestrationframework.This algorithm addressestheneedtoefficientlymanageresourcesanddynamicallyadjustthenum- ber ofcontainersbasedonworkloaddemands.Ouralgorithmincorporatescapacityplanning to determinethemaximumandminimumnumberofservicesreplicas(containers)thatcanbe deployedbasedonavailableresources,performancerequirements,andworkloadindynamical way. Our solutionisimplementedonasystemmanagingaservicebasedonDockerandSWARM Orchestration frameworks,includingtheuseofothertoolssuchas,Prometheus,cAcvisor,Apache Bench. Finally,theexperimentalresultshaveasignificantimpactontheavailability,waiting time, processing,andtotaltime(responsetime),ofaservicechargedconstantlywithanincreas- ing workload.enContainer ,FogComputing,Dockerswarm,ScalabilityMaster