Efficient Virtual Machine Placement for On-Demand Access to Infrastructure Resourcesin Cloud Computing
|
10.5120/11629-7101 |
Sameer Kumar Mandal and Pabitra Mohan Khilar. Article: Efficient Virtual Machine Placement for On-Demand Access to Infrastructure Resourcesin Cloud Computing. International Journal of Computer Applications 68(12):6-11, April 2013. Full text available. BibTeX
@article{key:article,
author = {Sameer Kumar Mandal and Pabitra Mohan Khilar},
title = {Article: Efficient Virtual Machine Placement for On-Demand Access to Infrastructure Resourcesin Cloud Computing},
journal = {International Journal of Computer Applications},
year = {2013},
volume = {68},
number = {12},
pages = {6-11},
month = {April},
note = {Full text available}
}
Abstract
Cloud computing is the utility computing that provides virtualized resources, applications, and services using distributed network and Internet. Cloud computing service offers the ability to scale up and scale down your computing requirements and most importantly to reduce the cost of deployment. Many organizations are migrating to cloud computing services to lower the risk and for better business continuity. In case of on-demand access user requests infrastructure services for immediate access and for a very short interval of time, they have to pay certain charge depending upon that duration. In cloud computing, infrastructure requests are served by the allocation of virtual machines to those requests; these virtual machines should be placed on the underlying hardware infrastructure called datacenter. In this paper we have proposed a model for the efficient allocation of virtual machines on the cloud infrastructure to reduce the allocation time and to optimize the resource utilization. The proposed model is simulated and its performance is compared with two other existing models.
References
- Chunye, G. , Jie, L. , Qiang, Z. , Chen, H. and Zhenghu, G. 2010. The Characteristics of Cloud Computing. 39th International Conference on Parallel Processing Workshop. IEEE Computer Society, 1530-2016.
- Boss, G. , Malladi, P. , Legregni, L. and Hall, H. 2007 how a business can use cloud computing to reduce cost. IBM white paper.
- Zhang, S. , Zhang, S. , Chen, X. and Huo, X. 2010. Cloud Computing Research and Development Trend. 2nd International Conference on Future Networks.
- Sosinsky, B. 2012. Cloud Computing Bible. Wiley Publishing Inc.
- Mell, P. and Grance, T. 2011. The NIST Definition of Cloud Computing. NIST Special Publication, 800-145.
- Mills, K. , Filliben, J. and Dabrowski, C. 2011. Comparing VM-Placement Algorithms for On-Demand Clouds. Third IEEE International Conference on Cloud Computing Technology and Science. IEEE Computer Society, 978-0-7695-4622-3.
- Endo, P. T. and Goncalves, G. , E. 2010. A Survey on Open-Source Cloud Computing Solutions. VIII Workshop on Clouds, Grid Applications.
- Sadashiv, N. and Kumar, S. 2011. Cluster, Grid and Cloud Computing: A Detailed Comparison. The 6th International Conference on Computer Science & Education (August 3-5). ,SuperStar Virgo, Singapore.
- Sotomayor, B. , Montero, R. S. , Llorente, I. M. and Foster, I. 2009. Internet Computing IEEE (Sept. -Oct. ). Volume 13, Issue: 5, page(s) 14-22.
- Kim, H. , Kim, W. , Lee, K. , Newby, G. B. and Kim, Y. 2009. Experimental Study to Improve Resource Utilization and Performance of Cloud Systems based on Grid Middleware. KSII The first International Conference on Internet (December 2009).
- Zhong, H. , Tao, K. and Zhang, X. 2010. An Approach to Optimize Resource Scheduling Algorithm for Open-Source Cloud Systems. The Fifth Annual ChinaGrid Conference. IEEE Computer Society, 978-0-7695-4106-8.
- Patel, P. and Singh, A. K. 2012. A Survey on Resource Allocation Algorithms in Cloud Computing Environment. Golden Research Thoughts, Volume 2, Issue. 4 (Oct 2012), ISSN: 2231-5063.
- Zhang, Y. , Huang, G. , Liu, X. and Mei, H. 2010. Integrating Resource Consumption and Allocation for Infrastructure Resource on-Demand. IEEE 3rd International Conference on Cloud Computing. IEEE Computer Society, 978-0-7695-4130-3/10.
- OpenNebula. http://opennebula. org/about:about.
- The Eucalyptus. http://www. eucalyptus. com/eucalyptus-cloud.
- Peng, J. , Zhang, X. , Lei, Z. , Zhang, B. , Zhang, W. and Li, Q. 2009. Comparison of Several Cloud Computing Platform. Second International Symposium on Information Science and Engineering. IEEE Computer Society, 978-0-7695-3991-1/09.
- Gupta, A. , Milojicic, D. and Balle, S. M. 2012. HPC- Aware VM Placement in Infrastructure Clouds. Paralal Programming Laboratory. Department of Computer Science, University of Illinois.
- Calheiros, R. N. , Ranjan, R. , Beloglazov, A. , De Rose, C. A. F. and Buyya, R. 2011. CloudSim: A ToolKit for Modeling and Simulation of Cloud Computing Environment and Evaluation of Resource Provisioning Algorithm. http://www. cloudbus. org/cloudsim/.