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Load Balancing Approach in Cloud Computing using Improvised Genetic Algorithm: A Soft Computing Approach

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 122 - Number 9
Year of Publication: 2015
Authors:
Garima Joshi
S. K. Verma
10.5120/21729-4894

Garima Joshi and S K Verma. Article: Load Balancing Approach in Cloud Computing using Improvised Genetic Algorithm: A Soft Computing Approach. International Journal of Computer Applications 122(9):24-28, July 2015. Full text available. BibTeX

@article{key:article,
	author = {Garima Joshi and S. K. Verma},
	title = {Article: Load Balancing Approach in Cloud Computing using Improvised Genetic Algorithm: A Soft Computing Approach},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {122},
	number = {9},
	pages = {24-28},
	month = {July},
	note = {Full text available}
}

Abstract

The concept of Cloud computing has significantly changed the field of parallel and distributed computing systems. The major issues to the cloud are resource discovery, fault tolerance, load balancing, safety measure, task scheduling, dependability, data backup, and data portability. Load balancing is one of the essential responsibilities of the cloud computing. In current situation, the load balancing algorithms built should be very efficient in allocating the request. It also ensures the usage of the resources in an intelligent way so that underutilization or overutilization of the resources does not occur in the cloud environment. In this paper, a soft computing based load balancing approach has been proposed called Improvised Genetic Algorithm (IGA), for allocation of incoming jobs to the servers or virtual machines (VMs). The proposed algorithm considers the cost value as a fitness function, of an individual node while performing load balancing. The proposed strategy has been simulated using MATLAB toolkit.

References

  • Velte, A. T. , Veltey, T. J. , and Elsenpeter, R. , 2010, "Cloud Computing: A Practical Approach," Tata McGraw-Hill Education Private Limited, New Delhi, Edition.
  • Jadeja, Y. , and Modi, K. , 2012, "Cloud Computing-Concepts, Architecture and Challenges," International Conference on Computing, Electronics and Electrical Technologies, pages 877-880.
  • Shaikh, F. B. , and Haider, S. , 2011, "Security Threats in Cloud Computing", Internet Technology and Secured Transactions, 214-219.
  • Srinivas, J. , Reddy, K. V. S. , and Qyser, A. M. , July 2012, "Cloud Computing Basics", International Journal of Advanced Research in Computer and Communication Engineering, volume 1, issue 5.
  • Ray, S. , and Sarkar, A. D. , October 2012, "Execution Analysis of Load Balancing Algorithms in Cloud Computing Environment," International Journal of Cloud Computing Services and Architecture, volume 2, issue 5.
  • Dasgupta,K. , Mandal, B. , Dutta, P. , Mondal, J. K. , Dam, S. , 2013, "A Genetic Algorithm (GA) based Load Balancing Strategy for Cloud Computing," International Conference on Computational Intelligence: Modeling Techniques and Applications (CIMTA), volume 10, page 340-347.
  • Sotomayor, B. , Montero, R. S. , Llorente, I. M. , and Foster, I. , 2009, "Virtual infrastructure management in private and hybrid clouds," in IEEE Internet Computing, vol. 13, no. 5, pages 14- 22.
  • Wang, S. C. , Yan, K. Q. , Liao, W. P. , Wang, S. S. , 2010, "Towards a Load Balancing in a three level cloud computing network," in Proc. Third International Conference Computer Science and Information Technology (ICCSIT), IEEE, vol. 1, pages 108—113.
  • Radojevic, B. , and Zagar, M. , 2011, "Analysis of issues with load balancing algorithms in hosted (cloud) environments," In Proc. 34th International Convention on MIPRO, IEEE.
  • Lars, K. , Andreas,T. , Erhard,R. , 2012, "Load Balancing for Map Reduce-based Entity Resolution", in Proc. 28th International Conference on Data Engineering (ICDE), IEEE, pages 618-629.
  • Gu, J. , Hu, J. , Zhao, T. , Sun, G. , January 2012, "A New Resource Scheduling Strategy Based on Genetic Algorithm in Cloud Computing Environment," journal of computers, vol. 7, NO. 1.
  • Jaroodi, Al. , Mohamed, N. , May 2011, "DDFTP: Dual-Direction FTP," in Proc. 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), IEEE, pages 504-503.
  • Nishant, Sharma, K. P. , Krishna, V. , Gupta, C. , Singh, KP. , Nitin, N. , and Rastogi, R. , March 2012, "Load Balancing of Nodes in Cloud Using Ant Colony Optimization," In Proc. 14th International Conference on Computer Modeling and Simulation (UKSim), IEEE, pages 3-8.
  • Brototi, M. , Dasgupta, K. , Dutta, P. , 2012, "Load Balancing in Cloud Computing using Stochastic Hill Climbing-A Soft Computing Approach", in Proc. 2nd International Conference on Computer, Communication, Control and Information Technology(C3IT).
  • Randles, M. , Lamb, D. , and Taleb-Bendiab, A. , April 2010, "A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing", Proceedings of 24th IEEE International Conference on Advanced Information Networking and Applications Workshops, Perth, Australia, pages 551-556.