VIRTUAL MACHINE PROVISIONING BASED ON QUALITY OF SERVICE PARAMETERS

Abstract

Cloud computing is the computing paradigm which delivers IT resources as a service; hence users arefree from setting up the infrastructure and managing hardware etc. Users can spend more time for things they are good at like development of new applications. But, there exists some problems associated to efficient provisioning and delivery of applications using Cloud-based IT resources. These barriers concern various levels such as workload modeling, virtualization, performance modeling, deployment, and monitoring of applications on virtualized IT resources and on solving these problems more customers will be attracted to use these application. In this thesis, a dynamic provisioning technique that meet deadlines, response time and rejection rate as quality of service targets, and can adapt to peak-to-peak workload changes related to applications to ease the adaptive management of system and offering end-users guaranteed Quality of Services (QoS) in large, autonomous, and highly dynamic environments is implemented efficiently. For handling deadlines, we have introduced heterogeneity in cloud computing environment. In the proposed approach, to ensure efficient access of virtual machines, we have introduced virtual machine groups. Behavior and performance of applications and Cloud-based IT resources are modeled to adaptively serve end-user requests. Workload information is used to supply intelligent input about system requirements to an application provisioner with limited information about the physical infrastructure which causes improvement in efficiency. The results shown in this thesis indicate that this provisioning technique detects changes in workload intensity that occurs over time and makes appropriate changes in allocations of multiple virtualized IT resources, meets different QoS targets.