Abstract
Virtual machine is one of the major areas of infrastructure as a service in cloud computing. The VM provision for service provider and user should be inexpensive. In last decades, number of scientists proposed various schemes. There is less opportunity for the service provider to use from the resource pooling. Cloud computing is providing hosting service over Internet, and to service provider, number of request of resource can be served using Internet. Recently, resource management is required to maintain autoscaling of resource and improving the efficiency of resource in cloud computing. There are various approaches available for workload predication that is based on single model approach. It is very critical to find the result on the basis of traditional model. Different methods and techniques were analyzed by us in order to identify the virtual machine allocation. We have defined a new dynamic resource allocation and policy-based improvement of the effective management of the resources. Our proposed implementation shows a better performance and improves the VM allocation with accuracy and less time consuming.
