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http://dx.doi.org/10.9709/JKSS.2011.20.4.139

Virtual Machine Provisioning Scheduling with Conditional Probability Inference for Transport Information Service in Cloud Environment  

Kim, Jae-Kwon (인하대학교 정보공학과)
Lee, Jong-Sik (인하대학교 정보공학과)
Publication Information
Journal of the Korea Society for Simulation / v.20, no.4, 2011 , pp. 139-147 More about this Journal
Abstract
There is a growing tendency toward a vehicle demand and a utilization of traffic information systems. Due to various kinds of traffic information systems and increasing of communication data, the traffic information service requires a very high IT infrastructure. A cloud computing environment is an essential approach for reducing a IT infrastructure cost. And the traffic information service needs a provisioning scheduling method for managing a resource. So we propose a provisioning scheduling with conditional probability inference (PSCPI) for the traffic information service on cloud environment. PSCPI uses a naive bayse inference technique based on a status of a virtual machine. And PSCPI allocates a job to the virtual machines on the basis of an availability of each virtual machine. Naive bayse based PSCPI provides a high throughput and an high availability of virtual machines for real-time traffic information services.
Keywords
Cloud Computing; Naive Bayse; Transport Information Services; Virtual Machine Provisioning; PSCPI;
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Times Cited By KSCI : 4  (Citation Analysis)
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