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Performance Analysis of Cloud under different Virtual Machine Capacity
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 68 - Number 8 |
| Year of Publication: 2013 |
| Authors: V. Suresh Kumar, M. Aramudhan |
10.5120/11596-6952
|
V. Suresh Kumar, M. Aramudhan . Performance Analysis of Cloud under different Virtual Machine Capacity. International Journal of Computer Applications. 68, 8 ( April 2013), 1-4. DOI=10.5120/11596-6952
Abstract
Cloud computing is an upcoming, novel, realistic paradigm to host and deliver internet services. Cloud computing helps to plan accurately for provisioning of hardware or software and also eradicates the need of high-priced computing hardware and maintenance. Using virtualization, clouds handle shared collection of physical resources in a huge user base having differing requirements. Hence, clouds are substitute for grids, clusters and supercomputers, but in challenging scientific computing workloads virtualization leads to performance penalties. This paper investigates cloud performance analysis under different Virtual Machine (VM) capacity. VM parameters like RAM and processors number are varied, and resource allocation, CloudSim debt and VM percentage used are also studied.
References
- Weiss. Computing in the clouds. NetWorker, 11(4):16–25, Dec. 2007.
- R. Buyya, C. S. Yeo, and S. Venugopal. Market-oriented cloud computing: Vision, hype, and reality for delivering IT services as computing utilities. In Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications, 2008.
- R. Buyya and M. Murshed, GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing, The Journal of Concurrency and Computation: Practice and Experience (CCPE), Volume 14, Issue 13-15, Wiley Press, Nov. -Dec. , 2002.
- Calheiros, R. N. , Ranjan, R. , De Rose, C. A. , & Buyya, R. (2009). Cloudsim: A novel framework for modeling and simulation of cloud computing infrastructures and services. arXiv preprint arXiv:0903. 2525.
- J. E. Smith and R. Nair. Virtual Machines: Versatile platforms for systems and processes. Morgan Kauffmann, 2005.
- Marston, S. , Li, Z. , Bandyopadhyay, S. , Zhang, J. , & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision Support Systems, 51(1), 176-189.
- M. A. Vouk, Cloud computing — issues, research and implementations, Journal of Computing and Information Technology 16 (4) (2008) 235–246.
- W3C, Web Services Glossary [cited 2009 April 3]; Available from: http://www. w3. org/TR/ws-gloss/.
- Marston, S. , Li, Z. , Bandyopadhyay, S. , Zhang, J. , & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision Support Systems, 51(1), 176-189.
- S. Ostermann, A. Iosup, N. Yigitbasi, R. Prodan, T. Fahringer, and D. Epema. A Performance Analysis of EC2 Cloud Computing Services for Scienti?c Computing. In Cloudcomp, 2009.
- Buyya, R. , Yeo, C. S. , Venugopal, S. , Broberg, J. , & Brandic, I. (2009). Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation computer systems, 25(6), 599-616.
- Zhang, Q. , Cheng, L. , & Boutaba, R. (2010). Cloud computing: state-of-the-art and research challenges. Journal of Internet Services and Applications, 1(1), 7-18.
- Quiroz, H. Kim, M. Parashar, N. Gnanasambandam, and N. Sharma. Towards Autonomic Workload Provisioning for Enterprise Grids and Clouds. Proceedings of the 10th IEEE/ACM International Conference on Grid Computing (Grid 2009), Banf, Alberta, Canada, October 13-15, 2009, IEEE Computer Society Press.
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