Analyzing Virtual Machine Live Migration in Application Data Context

Virtualization plays a very vital role in the big cloud federation. Live and Real-time virtual machine migration is always a challenging task in virtualized environment, different approaches, techniques and models have already been presented and implemented by many re- searchers. The aim of this work is to investigate various parameters of Real-time and live data migration of virtual machines in stateful and data context at the application level. The migration of one virtual machine to another requires some time depending on the network bandwidth, guest availability, hardware limitation overcomes, resource allocation, server reallocation, hypervisor compatibility and many more. To enhance and ensure the performance and optimization of the time this work presents the some analysis in the form of different time stacks in multiple piece of data stored in the virtual machines. To optimize the migration time virtual machine checkpoints are used in order to achieve the better results by using the xen hypervisor memory technique which dynamically allows the migration of the configured memory while the allocated memory could be discarded for a while. By this the bad memory remains un-migrated only the good memory consisting the used data would be migrated by means of Real-time.