CFP last date
20 December 2024
Reseach Article

Live Migration of Virtual Machines in Cloud Environment using Prediction of CPU Usage

by Vikas Malik, C. R. Barde
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 23
Year of Publication: 2015
Authors: Vikas Malik, C. R. Barde
10.5120/20691-3604

Vikas Malik, C. R. Barde . Live Migration of Virtual Machines in Cloud Environment using Prediction of CPU Usage. International Journal of Computer Applications. 117, 23 ( May 2015), 1-5. DOI=10.5120/20691-3604

@article{ 10.5120/20691-3604,
author = { Vikas Malik, C. R. Barde },
title = { Live Migration of Virtual Machines in Cloud Environment using Prediction of CPU Usage },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 23 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume117/number23/20691-3604/ },
doi = { 10.5120/20691-3604 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:00:09.803233+05:30
%A Vikas Malik
%A C. R. Barde
%T Live Migration of Virtual Machines in Cloud Environment using Prediction of CPU Usage
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 23
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The virtualization gives the power of partitioning the physical host in to multiple virtual machines. We can manage the number of active host and their power consumption by migrating the virtual machines according to their resource requirement and current status on that particular host. Service level agreement is the main thing and essential one for giving the reliable quality of service between customers and the data centers. Live migration of the virtual machines managing the over load and under loaded host which gives the ability of dynamic resource allocation on another host. Dynamic virtual machine consolidation and switching off the idle host allow data centers to minimize the resource and power consumption. The proposed technique will provide the ability of dynamic virtual machine consolidation using adaptive utilization threshold based o CPU usage prediction which can easily manage the high level of SLA and reduces the number of VM migrations in between the host. The validation of the proposed technique on multiple workload traces of the Planet lab servers.

References
  1. BP. Rimal, E. Choi, I. Lumb, A Taxonomy and, Survey of Cloud Computing Systems, Proceedings of the Fifth International Joint Conference on INC, IMS and IDC, pp. 4451, 2009.
  2. P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R. Neugebauer, I. Pratt, and A. Warfield, Xen and the Art of Virtualization, Proceedings of the nineteenth ACM symposium on Operating Systems Principles (SOSP03), pp. 164-177, 2003.
  3. A. Beloglazov and R. Buyya, Optimal Online Deterministic Algorithms and Adaptive Heuristics for Energy and Performance Efficient Dynamic Consolidation of Virtual Machines in Cloud Data Centers, Concurrency and Computation: Practice and Experience (CCPE), Vol. 24, pp. 1397-1420, 2012.
  4. H. Liu, H. Jin, X. Liao, L. Hu, and C. Yu, VMs live migration of Virtual Machine Based on Full System Trace and Replay, Proceedings of the 18th International Symposium on High Performance Distributed Computing (HPDC'09), pp. 101-110, 2009.
  5. A. B. Nagarajan, F. Mueller, Ch. Engelmann and S. L. Scott,Proactive Fault Tolerance for HPC with Xen Virtualization, Proceedings of the 21st ACM International Conference on Supercomputing (ICS07), pp. 23-32, 2007.
  6. X. Fan, WD. Weber, LA. Barroso, Power provisioning for a warehouse-sized computer, Proceedings of the 34th Annual International Symposium on Computer Architecture (ISCA 2007), pp. 13 23, 2007.
  7. D. Kusic, JO. Kephart, JE. Hanson, N. Kandasamy, G. Jiang, Powerand performance management of virtualized computing environments via lookahead control, In Proceedings of the International Conference on Autonomic Computing (ICAC), pp. 3-12, 2008.
  8. R. Nathuji and K. Schwan. Virtualpower: Coordinated power management in virtualized enterprise systems. ACM SIGOPS Operating Systems Review, 41(6):265278, 2007.
  9. D. Kusic et al. Power and performance management of virtualized computing environments via lookahead control. Cluster Computing, 12(1):115, 2009.
  10. A. Verma et al. pMapper: power and migration cost aware application placement in virtualized systems. In Proc. of the 9th ACM/IFIP/USENIX Intl. Conf. on Middleware, pages 243264, 2008.
  11. Kumar S, Talwar V, Kumar V, Ranganathan P, Schwan K. vManage: loosely coupled platform and virtualization management in data centers. Proceedings of the 6th international conference on Autonomic computing (ICAC 2009),Barcelona,Spain, 2009;127136.
  12. V. Malik, C. R. Barde, "Survey on Architecture of Leading Hypervisors and Their Live Migration Techniques", International Journal of Computer Science and Mobile Computing,IJCSMC, Vol. 3, Issue. 11, November 2014.
  13. Jung G, Joshi KR, Hiltunen MA, Schlichting RD, Pu C. A cost-sensitive adaptation engine for server consolidation of multitier applications. Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware (Middleware 2009), Urbana Champaign, IL, USA, 2009;120.
  14. M. Wang, X. Meng, L. Zhang, Consolidating Virtual Machines with Dynamic Bandwidth Demand in Data Centers, Proceedings of IEEE INFOCOM 2011 MINICONFERENCE, pp. 71-75, 2011.
  15. VMware Inc. VMware distributed power management concepts and use, 2010.
  16. Zhen Xiao, Senior Member, IEEE, Weijia Song, and QiChen, Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment,IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 6, June 2013.
  17. Fahimeh Farahnakian, Pasi Liljeberg, and Juha Plosila LiRCUP: Linear Regression based CPU Usage Prediction Algorithm for Live Migration of Virtual Machines in Data Centers 39th Euromicro Conference Series on Software Engineering and Advanced Applications 2013.
  18. Anton Beloglazov and Rajkumar Buyya, Energy Effcient Resource Management in Virtualized Cloud Data Centers, 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, 2010.
  19. K. S. Park, V. S. Pai, CoMon: a mostly-scalable monitoring system for PlanetLab, ACM SIGOPS Operating Systems Review, pp. 65-47,2006.
Index Terms

Computer Science
Information Sciences

Keywords

Virtualization resource utilization prediction live migration consolidation.