Factors Influencing Fog Computing Adoption Based on Quality of Results (QoR) For Heterogeneous Data Analysis: A Proposed Framework
Nur Hamezah Abdul Malic1, Tengku Adil Tengku Izhar2, Mohd Razilan Abdul Kadir3 

1Nue Hamezah Abdul Malic, Faculty of Information Management, Universiti Teknologi MARA UiTM, UiTM Selangor, Malaysia.
2Tengku Adil Tengku Izhar, Faculty of Information Management, Universiti Teknologi MARA UiTM, UiTM Selangor, Malaysia.
3Mohd Razilan Abdul Kadir, Faculty of Information Management, Universiti Teknologi MARA UiTM, UiTM Selangor, Malaysia.

Manuscript received on 14 March 2019 | Revised Manuscript received on 18 March 2019 | Manuscript published on 30 July 2019 | PP: 2760-2766 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2249078219/19©BEIESP | DOI: 10.35940/ijrte.B2249.078219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The rapid increase of data generated has brought challenges on data quality level. Fog computing in general has been supporting the requirements of end user devices that could not be met by cloud computing solution and it is acknowledged to have a major impact on how an organisation decides to adopt for preprocessing a huge amount of data being generated by the devices. Since IoT devices generating very heterogeneous and dynamic data, there are challenges for the level of data quality. The limitation has hindered the development of fog systems framework that capable operating the dynamic execution of edge devices that handling generation and collection large amounts of data on-premise and off-premise. Thus,sufficient operations of identifying Quality of Result enable user to detect any problems when conducting the decision making. The aim of this paper is to address the factors that perceived likely to influence the adoption of fog computing in evaluating the data analysis on data transmitted from the ever increases devices.A conceptual framework has been constructed considering attributes such as heterogeneous data analysis (on-premise and off-premise) and Quality of Results (quality indicators, quality control, validity outcome and reliability outcome).Potential benefits from the implementation of this framework to organisation is it enable to provide greater value and benefits to the business process. The framework of this study could also be influencing and inhibiting the adoption of fog computing.Quality of result has higher chances to satisfy the defined industrial’s requirement. In addition, fog-computing adoption is important for serving an environment for industry to execute, monitor, and analyze a large form of data in a fog landscape.
Index Terms: Data Analysis, Fog Computing, Framework, Quality of Results.

Scope of the Article: Cloud Computing