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Conference Papers Year : 2010

Forecasting for Grid and Cloud Computing On-Demand Resources Based on Pattern Matching

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Abstract

The Cloud phenomenon brings along the cost-saving benefit of dynamic scaling. As a result, the question of efficient resource scaling arises. Prediction is necessary as the virtual resources that Cloud computing uses have a setup time that is not negligible. We propose an approach to the problem of workload prediction based on identifying similar past occurrences of the current short-term workload history. We present in detail the Cloud client resource auto-scaling algorithm that uses the above approach to help when scaling decisions are made, as well as experimental results by using real-world traces from Cloud and Grid platforms. We also present an overall evaluation of this approach, its potential and usefulness for enabling efficient auto-scaling of Cloud user resources.

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Dates and versions

hal-00758592 , version 1 (29-11-2012)

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Eddy Caron, Frédéric Desprez, Adrian Muresan. Forecasting for Grid and Cloud Computing On-Demand Resources Based on Pattern Matching. IEEE CloudCom 2010, Nov 2010, Indianapolis, Indiana, USA, United States. ⟨10.1109/CloudCom.2010.65⟩. ⟨hal-00758592⟩
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