CFP last date
20 January 2025
Reseach Article

I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers

by Praveen Shukla, R.K. Pateriya
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 123 - Number 9
Year of Publication: 2015
Authors: Praveen Shukla, R.K. Pateriya
10.5120/ijca2015905618

Praveen Shukla, R.K. Pateriya . I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers. International Journal of Computer Applications. 123, 9 ( August 2015), 28-32. DOI=10.5120/ijca2015905618

@article{ 10.5120/ijca2015905618,
author = { Praveen Shukla, R.K. Pateriya },
title = { I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 123 },
number = { 9 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 28-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume123/number9/21988-2015905618/ },
doi = { 10.5120/ijca2015905618 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:12:15.581454+05:30
%A Praveen Shukla
%A R.K. Pateriya
%T I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers
%J International Journal of Computer Applications
%@ 0975-8887
%V 123
%N 9
%P 28-32
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the advent of cloud computing in the arena of IT field energy consumption and service level agreement (SLA) violation emerge as a major problem, which reduces the profit of cloud service providers (CSP) and affect the cloud customers by fencing the reusability and scalability of the cloud data center services. This problem needs to be eradicate for the efficient resource provisioning in cloud data center. To satisfy the customer need virtual machine (VM) migration technique is required to balance the load of entire data center. Therefore we need to transfer the virtual machine of the overloaded host to the light weighted host using virtual machine migration technique. Due to frequent load balancing of cloud data center enormous amount of energy consumption takes place. This enhances the overall energy cost and degrades the performance of cloud data center. This paper proposes an Energy Efficient Dynamic VM Consolidation algorithm for reducing energy consumption.

References
  1. Jing Huang, Kai Wu, and Melody Moh, “Dynamic Virtual Machine Migration Algorithms Using Enhanced Energy Consumption Model for Green Cloud Data Centers,” © IEEE 2014.
  2. Kamyab khajehei, “Role of Virtualization in Cloud Computing,”International Journal of Advanced Research in Computer Science and Management Studies (ijarcsms),Volume 2, Issue 4, April 2014.
  3. P. Getzi Jeba Leelipushpam, and Dr. J.Sharmila, “Live VM Migration Techniques in Cloud Environment- A Survey,”IEEE Conference on Information and Communication Technologies (ICT) © 2013.
  4. Yatendra Sahu, R.K. Pateriya, and Rajeev Kumar Gupta, “Cloud Server Optimization with Load Balancing and Green Computing Techniques Using Dynamic Compare and Balance Algorithm,”5th International Conference on Computational Intelligence and Communication Networks© IEEE 2013.
  5. Linlin Wu, Saurabh Kumar Garg, Steve Versteeg, and Rajkumar Buyya, “SLA-Based Resource Provisioning for Hosted Software-as-a-Service Applications in Cloud Computing Environments,” IEEE Transactions on services computing, VOL. 7, NO. 3 JULY-SEPTEMBER 2014.
  6. C.L.Belady, “In the Data center, power and cooling costs more than the equipment it supports,” Nov. 2013.
  7. G. Chen, W. He, J. Liu, and S. Nath, “Energy-aware server provisioning and load dispatching for connection-intensive internet services,” in proceedings of the 5th USENIX symposium on networked system design and implementation, 2008.
  8. R. Nathuji, K. Schwan, “Virual power Coordinated power management in virtualized enterprise system,” Proc. of the ACM press, Dec. 2007.
  9. D. Kusic, J.O.Kephart, J.E.Hanson, et al. “Power and Performance Management of Virtualized Computing Environments via Look ahead Control,” Cluster Computing, Springer press, 2009.
  10. S. Srikantaiah, A. Kansal, F. Zhao, “Energy aware Consolidation for Cloud Computing,” Proc. USENIX Workshop on Power Aware Computing and Systems in Conjunction with OSDI, 2008.
  11. J. Stoess, C. Lang, F. Bellosa, “Energy Management for Hypervisor based Virtual Machines,” USENIX Annual Technical Conference on Proceedings, July 2007.
  12. A. Beloglazov, J. Abawajy, R. Buyya, “Energy-aware Resource Allocation Heuristics for Efficient Management of Data Centers for Cloud Computing,” Future Generation Computer Systems May 2012.
  13. A. Beloglazov, R. Buyya, “Optimal Online Deterministic Algorithms and Adaptive Heuristics for Energy and Performance Efficient Dynamic Consolidation of Virtual Machine in Cloud Data Center,” Concurrency and Computation Practice and Experience (CCPE), Wiley press Sep 2012.
  14. Zhibo Cao, Shoubin Dong, “Dynamic VM Consolidation for Energy-aware and SLA Violation Reduction in Cloud Computing,” 13th International Conference on Parallel and Distributed Computing, Applications and Technologies© IEEE 2012.
  15. R.N. calheiros, R.Ranjan, A.Beloglazov, and R.Buyya, “CloudSim a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms,” Software-practice and Experience, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud computing Cloud service provider (CSP) Energy consumption SLA violation Load balancing VM migration.