The week's pick
Random Articles
Reseach Article
Efficient Resources Allocation for Different Jobs in Cloud
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 56 - Number 10 |
| Year of Publication: 2012 |
| Authors: K. Dinesh, G. Poornima, K. Kiruthika |
10.5120/8928-3005
|
K. Dinesh, G. Poornima, K. Kiruthika . Efficient Resources Allocation for Different Jobs in Cloud. International Journal of Computer Applications. 56, 10 ( October 2012), 30-35. DOI=10.5120/8928-3005
Abstract
Cloud Computing is an emerging technique in recent years that provides computing as a services. In order to maximize resources utilization, many scheduling algorithms were analyzed and implemented. Job scheduling using Berger model is one of the algorithm for scheduling jobs. The combination of Berger model and Neural Network would overcome the disadvantage of Berger Model i. e. , incompletion of task when tasks-resources match is not achieved. In this work, the submitted jobs are classified based on different parameters like bandwidth, memory, Completion time and Resources Utilization. The classified user tasks are passed to the neural network. Neural network consists of input layer, hidden layer and output layer. With the help of hidden layer, the jobs are matched with the resources by adjusting weight. The performance of the system has been improved by means of efficient use of bandwidth, reducing a completion time which in turn improves resources utilization. CloudSim, a simulation tool has been used to simulate and the results shows reduced completion time and increased performance of the system.
References
- Peeyush Mathur, " Cloud Computing: New Challenge to the entire Computer Industry", international conference on Parallel, Distributed and Grid computing(PDGC), 2010.
- Vmware, "Virtualization Overview", online @ "vmware. com/pdf/virtualization. pdf".
- Baomin Xu, Chunyan Zhao , Enzhao Hu, Bin Hu, "Job Scheduling algorithm using Berger model in Cloud Environment" ,Elsevier in Advances in Engineering Software, Vol 42 , No. 7, Pp. 419-425, 2011.
- Ferguson D, Yemini Y, Nikolaou, "C. Microeconomic algorithms for load balancing in distributed computer systems", Proceedings of the eighth international conference on distributed systems, San Jose: IEEE Press, Vol. 2, No. 30, Pp. 491–9,1988.
- Kumaran Subramoniam, Muthucumaru Maheswaran and Michel Toulouse, "Towards a Micro-Economic Model for Resource Allocation in Grid Computing Systems" Electrical and Computer Engineering, IEEE CCECE, Vol. 2,Pp. 782- 785, 2002.
- Gomoluch J, Schroeder M. , "Market-Based resource allocation for Grid Computing: a model and simulation", In: Endler M, Schmidt D, editors. Proceedings of the first international workshop on middleware for Grid Computing (MGC 2003). Rio de Janeiro: Springer-Verlag, Vol. 6, No. 5, Pp. 211-218, 2009.
- Regev O, Nisan N, "The popcorn market – An online market for computational resources", Proceedings of the first international conference on information and computation economies Charleston: ACM Press, Vol. 28,No1–2, Pp. 177-189,2000.
- Carl G. Looney and Sergiu Dascalu, "A Simple Fuzzy Neural Network", University of Nevada Reno,Vol 9, issue 2, Pp 89557, 2009.
- Kothalil Gopalakrishnan Anilkumar and Thitipong Tanprasert, "Neural Network Based Priority Assignment for Job Scheduler", Faculty of science and Technology, Assumption University Bangkok, Thailland Vol 9, issue 3,pp-181-186.
- Udo Seiffert,"Artificial Neural Networks on Massively Parallel Computer Hardware", European Symposium on Artificial Neural Networks, pp. 319-330 april 2002.
- Asha Gowda Karegowda, A. S. Manjunath, M. A. Jayaram, "Application of Genetic Algorithm Optimized Neural Network Connection Weights for Medical Diagnosis of Pima Indiana Diabetes", International journal on soft computing(IJSC), Vol. 2, No. 2, May 2011.
- Maithili A, Vasantha kumara R, Rajamanickam S, "Neural Networks Cum Cloud Computing Approach in Diagnosis of Cancer", International Journal of Engineering Research and Application(IJERA), Vol. 2, Issue 2, pp. 428-435, Mar-Apr 2012.
- Rawtani R M, "Achieving Knowledge Management Through Cloud Computing", 8th Convention PLANNER 2012.
- Satish Narayana Srirama, Pelle Jakovits, Eero Vainikko, "Adapting Scientific Computing Problems to Clouds using MapReduce", Elsevier, may 2011.
- Venkatesa . Kumar V and Dinesh K,"Job Scheduling Using Fuzzy Neural Network in Cloud Environment",bonfring international journal of man machine interface, Vol 2, no 1, march 2012.
- Rajkumar Buyya, Rajiv Ranjan and Rodrigo N. Calheiros, "Modeling and simulation of scalable Cloud Computing environments and the CloudSim Toolkit: challenges and opportunities", Proceedings of the seventh high performance Computing and simulation conference(HPCS 2009, ISBN: 978-1- 4244-49071), Leipzig, Germany. New York, USA: IEEE Press, June 21–24, 2009.
Index Terms
Keywords