Performance Analysis of Live and Offline VM Migration Using KVM

Full Text (PDF, 334KB), PP.50-57

Views: 0 Downloads: 0

Author(s)

Garima Rastogi 1,* Rama Sushil 2

1. Department of Computer Science and Engineering, DIT University/Department, Dehradun, 248009, India

2. Department of Information Technology, DIT University/Department, Dehradun, 248009, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2016.11.07

Received: 12 Jul. 2016 / Revised: 23 Aug. 2016 / Accepted: 2 Oct. 2016 / Published: 8 Nov. 2016

Index Terms

Underutilized, Scalability, Portability, Fault tolerance, Total Migration Time, Downtime

Abstract

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.

Cite This Paper

Garima Rastogi, Rama Sushil, "Performance Analysis of Live and Offline VM Migration Using KVM", International Journal of Modern Education and Computer Science(IJMECS), Vol.8, No.11, pp.50-57, 2016. DOI:10.5815/ijmecs.2016.11.07

Reference

[1]R. Buyya, C. Vecchiola, S. T. Selvi. “Mastering Cloud Computing: Cloud Foundation and Applications Programming”, MK Publisher Edition 2013.
[2]M. Imran Alam, M. Pandey, S. S. Rautaray, “A Comprehensive survey on Cloud Computing”, International Journal of Information Technology and Computer Science, 02, pp. 68-79, 2015.
[3]M. Durairaj, P. Kannan, “A Study On Virtualization Techniques And challenges in cloud computing”, International Journal of Scientific and Technology Research, Vol-3, issue-11, pp 147-151, Nov 2014.
[4]N. el-Khameesy, H.A. Rahman, “A Proposed virtualization technique to enhance IT Services “,International Journal of Information Technology and Computer Science, 12, pp. 21-30, 2012.
[5]A. Rabiatul Addawiyah Mat Razali, A. Ruhani, Z. Norliza, S. Mustaffa, “Virtual Machine Migration Implementation in Load Balancing for Cloud Computing” , proceedings of IEEE conference Intelligent and Advanced Systems, (Kuala Lumpur), pp. 1-4, 2014.
[6]P. Getzi Jeba Leelipushpam, J. Sharmila, “Live VM Migration Techniques in Cloud Environment- A survey”, Proceedings of IEEE Conference on Information and Communication Technologies, (Je Ju Island), pp. 408-413, 2013.
[7]F. Salfner, P. Tröger, A. Polze , “Downtime Analysis of Virtual Machine Live Migration”, The Fourth International Conference on Dependability,(IARIA), pp. 100-105, 2011.
[8]W. Hu , A. Hicks , L. Zhang , E. M. Dow , V. Soni , H. Jiang , R. Bull , J. N. Matthews, “A quantitative study of virtual machine live migration”, Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference, (August 05-09, Miami, Florida, USA), 2013 .
[9]S. Akoush, R. Sohan, A. Rice,A. W. Moore, A. Hopper, “Predicting the Performance of Virtual Machine Migration”, IEEE proceedings of Modeling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS, Miami Beach, FL),, pp. 37-46, 2010.
[10]D. Kapil, E. S. Pilli, R. C. Joshi., “Live virtual machine migration techniques: Survey and research challenges”, IEEE proceedings of Advance Computing Conference , (Ghaziabad, India), pp. 963-969, 2013.
[11]M. R. Anala, M. Kashyap , G. Shobha, “Application performance analysis during live migration of virtual machines”, IEEE proceedings of Advance Computing Conference ( Ghaziabad, India), pp. 366-372, 2013.
[12]M. Zhao , R. J. Figueiredo, “Experimental study of virtual machine migration in support of reservation of cluster resources”, Proceedings of the 2nd international workshop on Virtualization technology in distributed computing, (Reno, Nevada), pp. 1-8, 2007.
[13]H. R. Prakash, M. R. Anala, G. Shobha, “Performance analysis of Transport Protocol during live migration of Virtual Machines”, Indian Journal of Computer Science and Engineering, Vol-2 no-5, pp. 715-722, 2011.
[14]A. Shribman, B. Hudzia, “Pre-Copy and Post-Copy VM Live Migration for Memory Intensive Applications”, Springer Lecture notes in Computer Sc., vol. 7640, pp. 539-547, 2013.
[15]A. Gupta, J. Kumar, D. J Mathew, S. Bansal, S. Banerjee , H. Saran, “Design and Implementation of the Workflow of an Academic Cloud”, Proceedings of the 7th International conference on databases in networked information systems Springer Lecture notes in computer science, pp. 16-25, 2011.
[16]Y. wu, M. Zhao, “Performance modeling of virtual machine live migration”, Proceedings of IEEE 4th international conference on cloud computing, pp. 492-499, 2011.
[17]X. Feng, J. Tang, X. Luo, Y. Jin, “A performance study of live VM migration technologies: Motion vs. XenMotion”, Proceedings of IEEE conference Communications and Photonics, Shanghai, pp. 1-6, 2011.
[18]Red Hat Inc. Kvm - kernel based virtual machine. Technical report, Red Hat Inc.,2009 https://www.redhat.com/en/resources/kvm-%E2%80%93-kernel-based-virtual-machine