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

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.