효율적인 클라우드 컴퓨팅을 위한 가상장비 할당 방법
The Allocation Method of Virtual Machines for Efficient Cloud Computing
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초록
Cloud computing is a general term for anything that involves delivering hosted services over the Internet. These services are broadly divided into three categories:Infrastructure-as-a-Service(IaaS), Platform-as-a-Service(PaaS) and Software-as-a-Service(SaaS). There is a problem due to the heterogeneity of cloud computing nodes. Energy use and job executing time of each virtual machines are vary to each machines. So it is required a new technical methods to solve this problems. In this paper, we suggested a method which can calculate the proper number of virtual machine participating the cloud computing tasks using the mathematical model in terms of energy use and job execution time. To verify the suggested method, we performed the performance evaluation. The results of performance evaluation showed that the suggested algorithm could decrease the energy use and execution time of cloud computing.
Abstract
Cloud computing is a general term for anything that involves delivering hosted services over the Internet. These services are broadly divided into three categories:Infrastructure-as-a-Service(IaaS), Platform-as-a-Service(PaaS) and Software-as-a-Service(SaaS). There is a problem due to the heterogeneity of cloud computing nodes. Energy use and job executing time of each virtual machines are vary to each machines. So it is required a new technical methods to solve this problems. In this paper, we suggested a method which can calculate the proper number of virtual machine participating the cloud computing tasks using the mathematical model in terms of energy use and job execution time. To verify the suggested method, we performed the performance evaluation. The results of performance evaluation showed that the suggested algorithm could decrease the energy use and execution time of cloud computing.
참고문헌 (7)
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- Sungkap Yeo, "Using Mathematical Modeling in Provisioning a Heterogeneous Cloud Computing Environment", pp.55~62 (2011)
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