Advanced Cloud Resource Consistency Service Using Virtual Migration in Big Data
Infrastructure as a Service (IaaS) cloud computing has transform the way we think of acquiring resources by introducing a simple change: allowing users to lease computational resources from the cloud provider’s datacenter for a short time by deploying virtual machines (VMs) on these resources. This new model raises new challenges in the design and development of IaaS middleware. One of those challenges is the need to deploy a large number (hundreds oreven thousands) of VM instances simultaneously. Once the VM instances are deployed, another challenge is to simultaneously take a snapping of many resources and transfer them to persistent storage to support management tasks, such as suspend-resume and migration. With datacenters growing rapidly and configurations becoming heterogeneous, it is important to enable efficient concurrent deployment and snapshotting that are at the same time hypervisor independent and ensure a maximum compatibility with different configurations. To intent addresses these challenges by proposing a virtual file system for load balancing algorithm specifically optimized for virtual machine image storage. It is based on a lazy transfer scheme coupled with object versioning that handles data in big data centers transparently in a hypervisor-independent fashion, ensuring high portability for different configurations.
Author Name: G. Jeeva, V. Poongodi and Dr.K. Thangadurai
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Keywords: Cloud Infrastructure, Big Data, Load Balancing Algorithm, Virtual System.