e-Infrastructure and e-Services for Developing Countries. 9th International Conference, AFRICOMM 2017, Lagos, Nigeria, December 11-12, 2017, Proceedings

Research Article

A User-Centric Decision Support Model for Cloud of Things Adoption Using Ellipsoidal Fuzzy Inference System

  • @INPROCEEDINGS{10.1007/978-3-319-98827-6_24,
        author={Ademola Olaniyi and Babatunde Akinkunmi and Olufade Onifade},
        title={A User-Centric Decision Support Model for Cloud of Things Adoption Using Ellipsoidal Fuzzy Inference System},
        proceedings={e-Infrastructure and e-Services for Developing Countries. 9th International Conference, AFRICOMM 2017, Lagos, Nigeria, December 11-12, 2017, Proceedings},
        proceedings_a={AFRICOMM},
        year={2018},
        month={8},
        keywords={Decision support Cloud computing Cloud of Things Internet of Things Ellipsoidal Fuzzy},
        doi={10.1007/978-3-319-98827-6_24}
    }
    
  • Ademola Olaniyi
    Babatunde Akinkunmi
    Olufade Onifade
    Year: 2018
    A User-Centric Decision Support Model for Cloud of Things Adoption Using Ellipsoidal Fuzzy Inference System
    AFRICOMM
    Springer
    DOI: 10.1007/978-3-319-98827-6_24
Ademola Olaniyi1,*, Babatunde Akinkunmi1,*, Olufade Onifade1,*
  • 1: University of Ibadan
*Contact email: ademola.olaniyi@gmail.com, ope34648@yahoo.com, olufadeo@gmail.com

Abstract

Cloud adoption for Internet of Things is gaining attention among researchers and organizations. The decision to choose a Cloud vendor is complicated and dynamic in nature. The majority of the existing Decision support systems designed to support migration to the Cloud have limitations. They mostly provide information to support evaluation and selection of vendors with cost being the main factor while some fundamental issues had been left unsupported. This work proposes a robust User-Centric Cloud of Things Decision Analytic Model using Ellipsoidal Fuzzy Inference System. The proposed model supports real time decision making process for the adoption of Cloud computing in Internet of Things by comparing User-defined Application demand and Cloud Decision attributes. The results of this work are expected to contribute to the acceptance of Cloud of Things services.