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IJMLC 2018 Vol.8(5): 460-465 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2018.8.5.729

The Impact of Knowledge Engineering and Cloud Computing Adoption on Business Driven IT

Tarek Kaddoumi, Khaled Elhabashy, Mohamed Diab, and Mohamed K. Watfa

Abstract—Organizations have high expectations for cloud computing to help them in accomplishing their Business Level Objectives (BLOs) and consequently change the landscape of the business boosting both the flexibility and the agility of the business processes. Cloud computing improves management availability by monitoring the operations and creating new virtual environments for a multiplex set of ubiquitous services which is also referred to as the Internet of Things. Business Driven IT Management (BDIM) is a way to manage business layers through business metrics that are aligned with IT metrics through a processes layer. This paper analyses the linkage between cloud computing and the BDIM metrics including organization’s cost, quality of service (QoS), and productivity. Some of the research questions that would be analyzed include the following: will the cloud be cost efficient? Will it affect business productivity? Or will it enhance the quality of services?

Index Terms—Knowledge engineering, cloud computing, bdim, quality of service, productivity, cost efficiency.

The authors are with the Faculty of Engineering and Information Sciences, University of Wollongong in Dubai, Dubai, UAE (e-mail: tk729@ uowmail.edu.au, Kmmeh954@ uowmail.edu.au, mhdha725@ uowmail.edu.au, MohamedWatfa@uowdubai.ac.ae).

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Cite: Tarek Kaddoumi, Khaled Elhabashy, Mohamed Diab, and Mohamed K. Watfa, "The Impact of Knowledge Engineering and Cloud Computing Adoption on Business Driven IT," International Journal of Machine Learning and Computing vol. 8, no. 5, pp. 460-465, 2018.

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


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