Bibliometric Analysis of Data Analytics Techniques in Cloud Computing Resources Allocation

Authors

  • Sello Prince Sekwatlakwatla North-West University, South Africa
  • Vusumuzi Malele North-West University, South Africa
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DOI:

https://doi.org/10.51519/journalisi.v6i3.782

Keywords:

Resource allocation, Data Analytics Techniques, Traffic prediction

Abstract

Cloud computing provides on-demand computing services over the Internet, allowing for quicker innovation, more flexible resources, and economies of scale while reducing the need for physical data centers and servers. With this benefit, most organizations are adopting this technology, and some organizations are also operating fully on cloud computing. This causes traffic to increase, and most of these organizations are struggling with resource allocation, resulting in complaints from users regarding inactive system performance, timeouts in applications, and higher bandwidth use during peak hours. In this regard, this study investigates data analytics techniques and tools for the allocation of resources in cloud computing. The study indexed journal articles from the Scopus Database and Web of Science (WOS) between 2010 and 2024. This article brings new insights into the analysis of data analytics techniques in Africa and collaborations with other developing countries. The findings present tools and approaches that may be used to allocate cloud computing resources and give recommendations.

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Published

2024-09-26

Issue

Vol. 6 No. 3 (2024): September

Section

Articles

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How to Cite

[1]
S. P. Sekwatlakwatla and V. Malele, “Bibliometric Analysis of Data Analytics Techniques in Cloud Computing Resources Allocation”, journalisi, vol. 6, no. 3, pp. 2037–2047, Sep. 2024, doi: 10.51519/journalisi.v6i3.782.

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