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|Title:||Investigating cloud adoption using influence diagrams as a decision support model||Authors:||Christoforou, Andreas
Andreou, Andreas S.
|Keywords:||Cloud adoption;Decision support;Fuzzy influence diagrams;Influence diagrams||Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Field:||Engineering and Technology||Issue Date:||Dec-2015||Publisher:||World Scientific Publishing Co.||Source:||International Journal on Artificial Intelligence Tools, 2015, vol. 24, no. 6||Journal:||International Journal on Artificial Intelligence Tools||Abstract:||The fact that Cloud Computing is steadily becoming one of the most significant fields of Information and Communication Technology (ICT) has led many organizations to consider the benefits of migrating their business operations to the Cloud. Decision makers are facing strong challenges when assessing the feasibility of the adoption of Cloud Computing for their organizations. Cloud adoption is a multi-level decision which is influenced by a number of intertwined factors and concerns thus characterizing it as a complex and difficult to model real-world problem. In this paper we propose two decision support modeling approaches based on Influence Diagrams (ID) aiming to model the answer to the question "Adopt Cloud Services or Not?" Two models are developed and tested, the first is a generic ID with nodes interacting in a probabilistic manner, while the second is a more flexible version that utilizes Fuzzy Logic. Both models combine several factors that influence the decision to be taken, which were identified through literature review and input received from field experts. The proposed approaches are validated using five experimental scenarios, two synthetic and three real-world cases, and their performance suggests that they are highly capable of supporting the right decision.||ISSN:||0218-2130||DOI:||10.1142/S0218213015600052||Rights:||© 2015 World Scientific Publishing Company.||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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