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Title |
Dynamic Resource Allocation Using Skewness Algorithm in Cloud Computing |
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Author |
D.Golden Jemi, C.S Soumiya |
| Citation |
Vol. 15 No. 1 pp. 82-87 |
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Abstract |
Cloud Computing is the latest technology used by many organizations in this competitive world. As many organizations are using cloud computing technology, the major issue is resource allocation as pay-per-use on demand basis. In Cloud environments, efficient resource provisioning and management is a challenging issue because of the dynamic nature of the Cloud and the need to satisfy heterogeneous resource requirements. In such dynamic environments where end-users can arrive and leave the Cloud at any time, a Cloud service provider should be able to make accurate decisions for scaling up or down its data-centers while taking into account several utility criteria, the delay of virtual resources setup, the migration of existing processes, the resource utilization. In order to satisfy parties, an efficient and dynamic resource allocation strategy is mandatory. Dynamic Resource Allocation dealing with virtualization machines on physical machines. The results confirmed that the virtual machine which loading becomes too high, it will automatically migrated to another low loading physical machine without service interrupting. This can be done with the help of Skewness Algorithm. The flexible resource provisioning and migrations of machine state have improved efficiency of resource usage and dynamic resource provisioning capabilities. Allocating virtual machine to an appropriate physical machine is important to enhance the performance of cloud computing environment |
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Keywords |
Virtualization, Cloud Computing, Load prediction, Hot spot mitigation, Green Computing, Resource Management |
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