Title: Live migration of virtual machines with their local persistent storage in a data intensive cloud

Authors: Abhinit Modi; Raghavendra Achar; P. Santhi Thilagam

Addresses: Cloud and Enterprise Division, Microsoft India Development Center, Hyderabad – 500032, India ' Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal – 575025, India ' Department of Computer Science and Engineering, National Institute of Technology Karnataka, Surathkal – 575025, India

Abstract: Processing large volumes of data to drive their core business has been the primary objective of many firms and scientific applications in these days. Cloud computing being a large-scale distributed computing paradigm can be used to cater for the needs of data intensive applications. There are various approaches for managing the workload on a data intensive cloud. Live migration of a virtual machine is the most prominent paradigm. Existing approaches to live migration use network attached storage where just the run time state needs to be transferred. Live migration of virtual machines with local persistent storage has been shown to have performance advantages like security, availability and privacy. This paper presents an optimised approach for migration of a virtual machine along with its local storage by considering the locality of storage access. Count map combined with a restricted block transfer mechanism is used to minimise the downtime and overhead. The solution proposed is tested by various parameters like bandwidth, write access patterns and threshold. Results show the improvement in downtime and reduction in overhead.

Keywords: data intensive cloud; live migration; local persistent storage; count maps; virtual machines; cloud computing; restricted block transfer; bandwidth; write access patterns; threshold.

DOI: 10.1504/IJHPCN.2017.083213

International Journal of High Performance Computing and Networking, 2017 Vol.10 No.1/2, pp.134 - 147

Received: 26 Jun 2015
Accepted: 28 Oct 2015

Published online: 22 Mar 2017 *

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