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Efficient Resource Utilization in Virtual Cloud Computing Environment

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Akshay Kumar Gupta, Pradeep S. Rawat
10.5120/ijca2017914541

Akshay Kumar Gupta and Pradeep S Rawat. Efficient Resource Utilization in Virtual Cloud Computing Environment. International Journal of Computer Applications 168(11):25-27, June 2017. BibTeX

@article{10.5120/ijca2017914541,
	author = {Akshay Kumar Gupta and Pradeep S. Rawat},
	title = {Efficient Resource Utilization in Virtual Cloud Computing Environment},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {168},
	number = {11},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {25-27},
	numpages = {3},
	url = {http://www.ijcaonline.org/archives/volume168/number11/27920-2017914541},
	doi = {10.5120/ijca2017914541},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Cloud computing is a platform that provides user to implement revolutionary technologies. The main phenomena of cloud computing is based on accessing the resources using remote computation. Task scheduling is one of the major area that should be focused on. In cloud environment there may be a condition where the resources are limited that may affect resource availability. This paper presents an Enhanced version of MaxMin task scheduling algorithm that improves the turnaround time. The tasks are divided in two groups and the larger task is assigned to the resource (virtual machine) with high mips rate and other task is assigned to resource with low mips rate. To perform the experiment CloudSim toolkit is used. Our result shows that the Enhanced MaxMin algorithm gives the better result.

References

  1. Rawat, Pradeep Singh, Anuj Kumar Yadav, and Varun Barthwal. "Grid resource computing environment simulation using GridSim toolkit." Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on. IEEE, 2015.
  2. Santhosh, B., and D. H. Manjaiah. "A hybrid AvgTask-Min and Max-Min algorithm for scheduling tasks in cloud computing." Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2015 International Conference on. IEEE, 2015.
  3. Hu, Jinhua, et al. "A scheduling strategy on load balancing of virtual machine resources in cloud computing environment." Parallel Architectures, Algorithms and Programming (PAAP), 2010 Third International Symposium on. IEEE, 2010.
  4. Kaur, Shaminder, and Amandeep Verma. "An efficient approach to genetic algorithm for task scheduling in cloud computing environment." International Journal of Information Technology and Computer Science (IJITCS) 4.10 (2012): 74.
  5. Rawat, Pradeep Singh et al. “Performance analysis of cloud computing environment and comparison with IaaS model using cloud analyst” Advances in Electronics Electrical and Computer Science Engineering, 2012.
  6. Calheiros, Rodrigo N., et al. "CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms." Software: Practice and experience 41.1 (2011): 23-50.

Keywords

CloudSim, MaxMin, Cloud computing, task scheduling, virtual machine , resource utilization, performance