Daleel:simplifying cloud instance selection using machine learning

Samreen, Faiza and El Khatib, Yehia and Rowe, Matthew Charles and Blair, Gordon Shaw (2016) Daleel:simplifying cloud instance selection using machine learning. In: Network Operations and Management Symposium (NOMS), 2016 IEEE/IFIP. Network Operations and Management Symposium (NOMS), 2016 IEEE/IFIP . IEEE. ISBN 9781509002238

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Abstract

Decision making in cloud environments is quite challenging due to the diversity in service offerings and pricing models, especially considering that the cloud market is an incredibly fast moving one. In addition, there are no hard and fast rules; each customer has a specific set of constraints (e.g. budget) and application requirements (e.g. minimum computational resources). Machine learning can help address some of the complicated decisions by carrying out customer-specific analytics to determine the most suitable instance type(s) and the most opportune time for starting or migrating instances. We employ machine learning techniques to develop an adaptive deployment policy, providing an optimal match between the customer demands and the available cloud service offerings. We provide an experimental study based on extensive set of job executions over a major public cloud infrastructure.

Item Type:
Contribution in Book/Report/Proceedings
Subjects:
ID Code:
77761
Deposited By:
Deposited On:
19 Jan 2016 08:50
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Oct 2020 07:52