• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.17-23
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• 2019

IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardwares. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy quickly by estimating costs for cloud infrastructures as soon as possible. However, swift response is not possible due to that cloud service providers provide a dozen or so hours delayed billing information. Our work proposes a realtime IaaS cost estimation model based on usages monitored by virtual machine instance. We operate PC laboratory service on a public cloud during full semester to validate our suggested model. From that experiment, an averaged disparity between estimation and actual cost is less than 5.2%.