Enhancing Cloud Scaling by Reducing Slow Data Migrations using Supervised Learning Approach

In the current era of computing world, the entire web based services and application are processed in the different cloud service vendors regions. The application/service specific processes are executed with the proper SLA segment which brings the access control over cloud users. When the user's application, services and resources are migrated from one network region to another region, the migration time factor is notified in the cloud service provider region. It helps to users and service provider to check how the services are migrated with the proper time span in the specific service access environment. The slow level data migrations are identified and the service regions may check the occurrences of slow migration and the cloud scaling need to be enhanced in the cloud service environment. The proposed work will be used to make the decisions towards eliminating the slow data migrations and increase the legibility level of cloud scaling factor.