Alkhalil, A., Sahandi, R. and John, D., 2016. A Review of the Current Level of Support to Aid Decisions for Migrating to Cloud Computing. In: ICC '16 International Conference on Internet of things and Cloud Computing, 22--23 March 2016, Cambridge, UK.
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Abstract
© 2016 Copyright held by the owner/author(s). Cloud computing provides an innovative delivery model that enables enterprises to reduce operational costs and improve flexibility and scalability. Organisations wishing to migrate their legacy systems to the cloud often need to go through a difficult and complicated decision-making process. This can be due to multiple factors including restructuring IT resources, the still evolving nature of the cloud environment, and the continuous expansion of the services offered. These have increased the requirement for tools and techniques to help the decision-making process for migration. Although significant contributions have been made in this area, there are still many aspects which require further support. This paper evaluates the existing level of support to aid the decision-making process. It examines the complexity of decisions, evaluates the current state of Decision Support Systems in respect of migrating to the cloud, and analyses three models that proposed support for the migration processes. This paper identifies the need for a coherent approach for supporting the whole decision-making process. Further, it explores possible new approaches for addressing the complex issues involved in decision-making for migrating to the cloud.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | © ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in 2016 Proceedings of the International Conference on Internet of things and Cloud Computing |
Uncontrolled Keywords: | Cloud computing; cloud migration; Decision-Making Process; cloud decision support; cloud knowledge base system |
Group: | Faculty of Science & Technology |
ID Code: | 24491 |
Deposited By: | Symplectic RT2 |
Deposited On: | 23 Aug 2016 14:52 |
Last Modified: | 14 Mar 2022 13:57 |
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