Performance evaluation of bandwidth for virtual machine migration in cloud computing. Issue 3 (2018)

• Record Type: Journal Article
• Authors: Bhardwaj, Aditya; Krishna, C. Rama
• Is Part Of: International journal of knowledge engineering and data mining. Volume 5:Issue 3(2018)
• Page Start: 139
• Page End: 152
• Publication Date: 2018
• Subjects: cloud computing -- virtualisation -- pre-copy -- migration time -- downtime -- KVM hypervisor; Knowledge representation (Information theory) -- Periodicals; Data mining -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-2087

Abstract

The proliferation of virtualisation enables cloud computing industries, such as Amazon, IBM, Google, Microsoft, and Rackspace to increase their physical hardware utilisation by multi-tenant model. One important key characteristic of server virtualisation is virtual machine (VM) migration. With the popularity of cloud paradigm, the number of enterprise applications deployed over cloud-systems are increasing. This shift in cloud services has brought new challenges of frequently varying resource requirement by the VM migration operation. Inaccurate allocation of bandwidth may affect end-user experience and reduce the cloud service provider's profit, Therefore, in this work we setup QEMU-KVM cloud VM migration experimental testbed environment and run CPU, memory intensive cloud benchmarks on the migrated VM. From the experimental results, it is found that increase in bandwidth significantly lower the migration time and downtime up-to an extent, however, reserving maximum bandwidth does not help anymore for performance improvement of migration mechanism.