Forecasting for Cloud computing on-demand resources based on pattern matching

Abstract : The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. Knowledge in advance is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose a new approach to the problem of workload prediction based on identifying similar past occurrences to the current short-term workload history. We present in detail the auto-scaling algorithm that uses the above approach as well as experimental results by using real-world data and an overall evaluation of this approach, its potential and usefulness.
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https://hal.inria.fr/inria-00460393
Contributor : Adrian Muresan <>
Submitted on : Wednesday, October 19, 2011 - 4:15:18 PM
Last modification on : Friday, April 20, 2018 - 3:44:24 PM
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Eddy Caron, Frédéric Desprez, Adrian Muresan. Forecasting for Cloud computing on-demand resources based on pattern matching. [Research Report] RR-7217, INRIA. 2010, pp.26. ⟨inria-00460393v3⟩

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