Energy Efficient Cloud Resource Management Frame work Using Machine Learning Techniques

Abstract

newline i newlineABSTRACT newlineCloud uses internet for achieving and developing latest innovation by newlineusing remote resources and deployed application with less expensive. The newlinemain requirement of the cloud provider is to provide the services and use the newlineresources like storage, networking and computing with adequate capacity. newlineThese resources consume enough energy during the interaction. The newlineenergy consumption model issues are solved by existing techniques with newlinespecific resource level. Cloud suffers a performance related problem because newlineof the idle energy consumption. This problem also leads the excess energy newlineduring minimum and idle workload situation. newlineThis problem is addressed by identifying and deleting from the cloud newlineinfrastructure in order to minimize the energy. The minimum energy workload newlineare moved to other host which is suitable for handling the workload i.e. newlinemigration. The migration process uses the agent based model by assessing the newlineenergy level of the resources in the cloud such as VM (Virtual Machine), Host newlineand Data center. Single agent model has the ability to evaluate only particular newlineresources so it doesn t support real-time situations