CFP last date
22 April 2024
Reseach Article

Hybrid Approach for Resource Scheduling in Green Clouds

by Keffy Goyal, Supriya Kinger
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 17
Year of Publication: 2013
Authors: Keffy Goyal, Supriya Kinger
10.5120/12979-0201

Keffy Goyal, Supriya Kinger . Hybrid Approach for Resource Scheduling in Green Clouds. International Journal of Computer Applications. 74, 17 ( July 2013), 33-37. DOI=10.5120/12979-0201

@article{ 10.5120/12979-0201,
author = { Keffy Goyal, Supriya Kinger },
title = { Hybrid Approach for Resource Scheduling in Green Clouds },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 17 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number17/12979-0201/ },
doi = { 10.5120/12979-0201 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:42:34.115305+05:30
%A Keffy Goyal
%A Supriya Kinger
%T Hybrid Approach for Resource Scheduling in Green Clouds
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 17
%P 33-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Task scheduling is very effective issue of green Cloud computing which is used for minimization of energy consumption and for minimization of execution time. To save the power, temperature aware resource scheduler is used. It contains all features that satisfy its users and fill all task requirements. Cloud computing uses the concept of virtualization for energy efficient programs. Temperature aware resource scheduling can provide green enhancement within Cloud computing environment. In proposed algorithm the scheduler allocate the task to that machine which is far from its critical temperature as well as it consume less power. The proposed work is on a hybrid approach for both temperature and power aware resource scheduling.

References
  1. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, G. Lee, D. A. Patterson, A. Rabkin,I. Stoica, and M. Zaharia, Above the Clouds : A Berkeley View of Cloud Computing, 2009.
  2. S. Srikantaiah, A. Kansal, and F. Zhao, "Energy aware consolidation for cloud computing," Cluster Computing, vol. 12, pp. 1–15, 2009.
  3. Andrew J. Younge et al. "Efficient Resource Management for Cloud Computing Environments" 978-1-4244-7614-5/10/$26. 00 ©20 1 0 IEEE.
  4. Anton Beloglazov et al "Energy Efficient Allocation of Virtual Machines in Cloud Data Centers" 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.
  5. S. Clearwater, Market-Based Control: A Paradigm for Distributed Resource Allocation, World Scientific.
  6. Anton Beloglazov et al "Energy Efficient Allocation of Virtual Machines in Cloud Data Centers" 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.
  7. Shailesh S. Deore et al. " Energy-Efficient Job Scheduling and Allocation Scheme for Virtual Machines in Private Clouds" International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 5– No. 1, January 2013 – www. ijais. org.
  8. Lizhe Wang et al. "Task scheduling with ANN-based temperature prediction in a data center: a simulation-based study" Engineering with Computers (2011) 27:381–391 DOI 10. 1007/s00366-011-0211-4.
  9. Lizhe Wang et al. "Thermal aware workload placement with task-temperature profiles in a data center" © Springer Science+Business Media, LLC 2011.
  10. J un Yang et al. "Dynamic Thermal Management through Task Scheduling" NSF grants CCF-0734339, CNS-0720595, OISE-0340752 and CCF-0641177.
  11. Zhang S, Chatha KS (2007) Approximation algorithm for the temperature-aware scheduling problem. In: ICCAD, pp 281–288
  12. J. Choi, C. -Y. Cher, H. Franke, H. Hamann, A. Weger, and P. Bose. ,Thermal-aware task scheduling at the system software level, In ISLPED, 2007.
  13. M. Gomaa, M. D. Powell, and T. N. Vijaykumar, Heat-and-Run: leveraging SMT and CMP to manage power density through the operating system, in ASPLOS, 2004
  14. A. K. Coskun, T. S. Rosing and K. Whisnant, Temperature Aware Task Scheduling in MPSoCs, in DATE, 2007
  15. Qinghui Tang, S. K. S. Gupta and G. Varsamopoulos, Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approach, IEEE Transactions on Parallel and Distributed Systems, vol. 19, no. 11, pp. 1458-1472, Nov 2008
  16. Y. Xie and W. Hung, Temperature-Aware Task Allocation and Scheduling for Embedded Multiprocessor System-on-Chip (MPSoC) Design, Journal of VLSI Signal processing 45, 2006
Index Terms

Computer Science
Information Sciences

Keywords

Green computing Resource scheduling Task scheduling Temperature Thermal management