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A Systematic Mapping Study of Cloud Large-Scale Foundation—Big Data, IoT, and Real-Time Analytics

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Data Management, Analytics and Innovation

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1042))

Abstract

Cloud computing is a unique concept which makes analysis and data easy to manipulate using large-scale infrastructure available to Cloud service providers. However, it is sometimes rigorous to determine a topic for research in terms of Cloud. A systematic map allows the categorization of study in a particular field using an exclusive scheme enabling the identification of gaps for further research. In addition, a systematic mapping study can provide insight into the level of the research that is being conducted in any area of interest. The results generated from such a study are presented using a map. The method utilized in this study involved analysis using three categories which are research, topic, and contribution facets. Topics were obtained from the primary studies, while the research type such as evaluation and the contribution type such as tool were utilized in the analysis. The objective of this paper was to achieve a systematic mapping study of the Cloud large-scale foundation. This provided an insight into the frequency of work which has been carried out in this area of study. The results indicated that the highest publications were on IoT as it relates to model with 12.26%; there were more publications on data analytics as is relates to metric with 2.83%, more articles on big data in terms of tool, with 11.32%, method with 9.43% and more research carried out on data management in terms of process with 6.6%. This outcome will be valuable to the Cloud research community, service providers, and users alike.

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Acknowledgements

We acknowledge the support and sponsorship provided by Covenant University through the Centre for Research, Innovation and Discovery (CUCRID).

Author information

Authors and Affiliations

  1. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Isaac Odun-Ayo, Rowland Goddy-Worlu & Temidayo Abayomi-Zannu

  2. School of Electrical Engineering and Computer Science, University of North Dakota, Grand Forks, USA

    Emanuel Grant

Authors
  1. Isaac Odun-Ayo
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  2. Rowland Goddy-Worlu
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  3. Temidayo Abayomi-Zannu
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  4. Emanuel Grant
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Corresponding author

Correspondence to Isaac Odun-Ayo .

Editor information

Editors and Affiliations

  1. Society for Data Science, Pune, Maharashtra, India

    Neha Sharma

  2. A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata, West Bengal, India

    Amlan Chakrabarti

  3. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

Appendix 1: List of Primary Studies

Appendix 1: List of Primary Studies

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Odun-Ayo, I., Goddy-Worlu, R., Abayomi-Zannu, T., Grant, E. (2020). A Systematic Mapping Study of Cloud Large-Scale Foundation—Big Data, IoT, and Real-Time Analytics. In: Sharma, N., Chakrabarti, A., Balas, V. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 1042. Springer, Singapore. https://doi.org/10.1007/978-981-32-9949-8_24

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