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Reseach Article

Energy-Efficient Job Scheduling and Allocation Scheme for Virtual Machines in Private Clouds

by Shailesh S. Deore, Ashok Narayan Patil
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 1
Year of Publication: 2013
Authors: Shailesh S. Deore, Ashok Narayan Patil
10.5120/ijais12-450842

Shailesh S. Deore, Ashok Narayan Patil . Energy-Efficient Job Scheduling and Allocation Scheme for Virtual Machines in Private Clouds. International Journal of Applied Information Systems. 5, 1 ( January 2013), 56-60. DOI=10.5120/ijais12-450842

@article{ 10.5120/ijais12-450842,
author = { Shailesh S. Deore, Ashok Narayan Patil },
title = { Energy-Efficient Job Scheduling and Allocation Scheme for Virtual Machines in Private Clouds },
journal = { International Journal of Applied Information Systems },
issue_date = { January 2013 },
volume = { 5 },
number = { 1 },
month = { January },
year = { 2013 },
issn = { 2249-0868 },
pages = { 56-60 },
numpages = {9},
url = { https://www.ijais.org/archives/volume5/number1/412-0842/ },
doi = { 10.5120/ijais12-450842 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T16:00:56.523169+05:30
%A Shailesh S. Deore
%A Ashok Narayan Patil
%T Energy-Efficient Job Scheduling and Allocation Scheme for Virtual Machines in Private Clouds
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 5
%N 1
%P 56-60
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud Computing is a promising paradigm in deployment of software and there survive. Computer researcher says a magnificent sentence, cloud computing is next generation operating system. Technologies such as cluster, grid, and now, cloud computing, have all aimed at allowing entrance to large amounts of computing power in a fully virtualized, para-virtulized manner. The Energy efficiency of information and communication technology becomes more and more vital due to elevate of energy costs and the world wide desire to decrease CO2 emissions [13],[14]. In this paper we argues energy-efficient job scheduling and allocation scheme that minimize number of hosts, so amount of energy conserve.

References
  1. Andreas Berl, Hermann de Meer, "A virtualized energy-efficient office environments", e-Energy 10, 2010, Apr 13-15, pp. 11-20.
  2. Jiandun Li, Junjie Peng, Wu Zhang,"A Scheduling Algorithm for Private Clouds", Journal of Convergence Information Technology,2011, Volume 6, Number 7,pp. 1-9.
  3. Saurabh Kumar Garg, Chee Shin Yeo, Arun Anandasivam, Rajkumar Buyya, "Environment-conscious scheduling of HPC applications on distributed cloud-oriented data centers ", Journal of Parallel and Distributed Computing, 2011,vol. 71, no. 6, 732-749.
  4. Akshat Verma, Puneet Ahuja, Anindya Neogi, "Power-aware dynamic placement of HPC applications",2008, Proceedings of the 22nd International Conference on Supercomputing (ICS'08),Island of Kos, pp. 175-184.
  5. Gregor von Laszewski, LizheWang, Andrew J. Younge ,Xi He ,"Power-Aware Scheduling of Virtual Machines in DVFS-enabled clusters", cluster 09 IEEE international on Cluster , 2009, pp. 1-11.
  6. Aman kansal, Feng Zhao, jie Liu, Nupur Kothari, Arka A. Bhattacharya , "Virtual machine power metering and provisioning", copyright 2010 ACM, 2010.
  7. Tami Tamir, "Scheduling with bully selfish jobs", Theory of Comput Syst, vol. 50, no. 1, 2012, pp. 124-146.
  8. Pradeep Kumar Sharma, Chandana Das," Energy efficient scheduling in cloud computing ", Inventi Impact: Cloud Computing,2012.
  9. Shailesh Deore, A. N. Patil, Ruchira Bhargava," Systematic Review of energy efficient scheduling techniques in cloud computing" International journal of computer application,Vol. 52, 2012, Number 15.
  10. Shailesh Deore, A. N. Patil, Ruchira Bhargava,"Energy Efficient Scheduling Scheme for virtual machines in cloud computing" International journal of computer application, Vol. 56, 2012, Number 10.
  11. Juan Manuel Ramrez-Alcaraz, Andrei Tchernykh, Ramin Yahyapour, Uwe Schwiegelshohn, Ariel Quezada-Pina, Jose Luis Gonzalez-Garca, and Adan Hirales-Carbajal, "Job allocation strategies with user run time estimates for online scheduling in hierarchical grids", J. Grid Comput. , ,2012, October 10,pp. 95-116.
  12. Virtual Box available on www. virtualbox. org
  13. Ismael Solis Moreno, Jie Xu, "Energy-Efficiency in cloud Computing Environments : Towards Energy Saving without Performance degradation",In International Journal of Cloud appliocation and Computing, Vol. 1, Issue. 1, 2011, pp. 17-33.
  14. R. Buyya, Beloglazov A. , Abwajy J. ,"Energy-Effcient Mangement of Data Center Resources for Cloud Computing: A vision, Architectural elements, and open Challenges " In proc. Of 2010 International conference on parallel and Distributed Processing Techniques and Application, las Vegas, NV, USA.
  15. Francesc Guim, Ivan Rodero, Julita Corbalan, A. Goyeneche, "The Grid Backfilling:A Multi-site data mining architecture with data mining prediction techniques",2008, Grid middleware and services,published by Spinger US, pp. 137-152
  16. Joulemeter1. 2 available on: http://research. microsoft. com/en-us/default. aspx
  17. I. Foster, "The grid: Computing without bounds " , In scientific Journal , Vol. 288, No. 4, pp. 78-85.
  18. D. Tsafrir, Y. Etsion, and D. G. Feitelson," Backfilling using system-generated predictions rather than user runtime estimates" In the IEEE TPDS, 2006.
  19. Y. Zhang, W. Sun, and Y. Inoguchi," Cpu load predictions on the computational grid", Cluster and Grid computing, 2006.
  20. R. V. Patil, K. C. Jondhale 2010 , " Edge based technique to estimate number of clusters in k-means color image segmentation", IEEE Internatinal conference on Computer Sciene and Information Technology, Chengdu , China, vol. 2, pp. 117-121.
  21. P. S. Patil, S. R. Kolhe, R. V. Patil, P. M. Patil , "Performance Evaluation in Iris Recognition and CBIR System based on phase congruency", International Journal of Computer Applications, Vol. 47(14),2012, pp. 13-18.
Index Terms

Computer Science
Information Sciences

Keywords

Energy Virtual energy efficient Workload VM VM request