Forecasting for Cloud computing on-demand resources based on pattern matching
Résumé
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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RR-7217.pdf (620.49 Ko)
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errorscaling.jpg (18.21 Ko)
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lcg.jpg (56.6 Ko)
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lcg_pattls.jpg (31.49 Ko)
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nordugrid.jpg (52.5 Ko)
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nordugrid_pattls.jpg (32.1 Ko)
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sharcnet.jpg (64.17 Ko)
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sharcnet_pattls.jpg (27.02 Ko)
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| Format | Figure, Image |
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| Format | Figure, Image |
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