Rama Sushil

Work place: Department of Information Technology, DIT University/Department, Dehradun, 248009, India

E-mail: ramasushil@yahoo.com


Research Interests: Autonomic Computing, Distributed Computing, Data Structures and Algorithms, Mathematics of Computing


Prof (Dr) Rama Sushil currently working as prof and head, Department of Information Technology, DIT University, Dehradun. She has completed PhD from IIT Roorkee, Uttarakhand, (INDIA). She has guided various PhD students. She has also authored chapters in the books of IGI Global and published more than 40 research papers. Her research interests are Cloud Computing, Mobile Agents and Distributed Computing.

Author Articles
Performance Analysis of Live and Offline VM Migration Using KVM

By Garima Rastogi Rama Sushil

DOI: https://doi.org/10.5815/ijmecs.2016.11.07, Pub. Date: 8 Nov. 2016

Virtualization is a core technology used for the implementation of cloud computing. It increases the utilization of resources such as processor, storage, network etc. by collecting various underutilized resources available in the form of a shared pool of resources built through the creation of Virtual Machines (VMs).
The requirements in cloud environment are dynamic therefore there is always a need to move virtual machines within the same cloud or amongst different clouds. This is achieved through migration of VMs which results in several benefits such as saving energy of the host, managing fault tolerance if some host is not working properly and load balancing among all hosts. In this experimental study, effort has been made to analyze the performance of offline and live VM migration techniques with respect to total migration time and downtime of VM migration. Kernel-based Virtual Machine (KVM) hypervisor has been used for virtualization and a series of experiments have been carried out in computer service center of IIT Delhi on their private cloud Baadal. The experiment results show that downtime during live migration is very less in comparison to the offline migration while the total migration time is more in comparison to the offline migration.

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