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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Rapport
[Research Report] RR-7217, INRIA. 2010, pp.26
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https://hal.inria.fr/inria-00460393
Contributeur : Adrian Muresan <>
Soumis le : mercredi 19 octobre 2011 - 16:15:18
Dernière modification le : vendredi 20 avril 2018 - 15:44:24
Document(s) archivé(s) le : dimanche 4 décembre 2016 - 19:10:45

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  • HAL Id : inria-00460393, version 3

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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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