An Efficient Technique for Cloud Resource Management Using Machine Learning Model

Resource management is a vital process in the cloud for satisfying the customer requirement. Resources get the task from the user and perform necessary action. The task needs the data which are collected from various environments. The existing systems are not concentrating on the data but it maps the request to the resources. Resource level management provides the service response to the user. It suffers the data related issues, so it is solved by incorporate the efficient machine learning over the cloud. The proposed model classifies the dataset based on the workload condition namely GPU and CPU level. The model also developed related to the workload. The resources from the cloud are provisioning and allocate to the specific region with necessary parameters. Dynamic load assignment helps to the user for keeping the cost in their acceptable level. Various machine and deep learning models have been analysed related to workload parameters. It achieves high efficient resource monitoring in order to handle faulty resource and make then to active level.