Neural Network Based Resource Allocation using Run Time Instrumentation with Virtual Machine Migration in Cloud Computing
Anitha N1, Anirban Basu2
1Anitha N, Research Scholar VTU, Department of ISE, EPCET, Karnataka, Bangalore, India.
2Dr. Anirban Basu, Research Head, Department of CSE, EPCET, Karnataka, Bangalore, India.
Manuscript received on January 12, 2015. | Revised Manuscript received on January 13, 2015. | Manuscript published on January 25, 2015. | PP:27-29 | Volume-3 Issue-3, January 2015. | Retrieval Number: C0901013315
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The enterprise level and the market level both are seeing a huge growth in the cloud computing. The resource is accessed in a large with better way and also globally. An individual or organization can lease the computational or storage resources, in return reducing the cost of the infrastructure. The resources optimization is one of the major issue faced in the cloud computing for the cloud service providers. Most of the optimization of resources allocation is done after the calculation of the resources needed and on the go. In this paper, a mathematical system model for the resource allocation using neural network with run time instrumentation has been proposed. The proposed model shows the better resource utilization.
Keywords: Cloud Computing, Deep Inspection, Instrumentation, Machine Learning, Neural Network,