Abstract: In the era of Cloud computing where it utilizes Infrastructure as a Service (IaaS), elasticity has become one of the very essential components for providing better Quality of Services (QoS). The concept of elasticity ensures an effective and dynamic resource allocation during sudden changes of workloads in Virtual Machines (VMs). The current research trends highlight that there are very less efficient virtualized environments for proper task scheduling in the field of cloud computing. Therefore effective resource management/provisioning during overload of jobs in the distributed virtual machines have become one of the most challenging tasks. It can be seen that most of the existing techniques cannot respond rapidly when the work load associated with a particular service amplifies. Most of the exiting trends are found to have inaccuracy in case of taking proper decisions which results problems during resources provisioning in cloud services. In this study an efficient Instant Time Resource Provisioning Prototype (ITRP) has been introduced which increases the scalability of allocating resources during each alteration cycle when work load increases. The performance analysis of the proposed system shows that it achieves very accuracy in achieving speed up for resource provisioning in cloud infrastructures as compare to the existing models.

Keywords: Resource Provisionong , Cloud Computing , Virtual Machines.