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A comprehensive and systematic literature review on the big data management techniques in the internet of things
The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664750/ http://dx.doi.org/10.1007/s11276-022-03177-5 |
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author | Naghib, Arezou Jafari Navimipour, Nima Hosseinzadeh, Mehdi Sharifi, Arash |
author_facet | Naghib, Arezou Jafari Navimipour, Nima Hosseinzadeh, Mehdi Sharifi, Arash |
author_sort | Naghib, Arezou |
collection | PubMed |
description | The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for BDM in IoT. This paper aims to study the important mechanisms in this area systematically. This paper studies articles published between 2016 and August 2022. Initially, 751 articles were identified, but a paper selection process reduced the number of articles to 110 significant studies. Four categories to study BDM mechanisms in IoT include BDM processes, BDM architectures/frameworks, quality attributes, and big data analytics types. Also, this paper represents a detailed comparison of the mechanisms in each category. Finally, the development challenges and open issues of BDM in IoT are discussed. As a result, predictive analysis and classification methods are used in many articles. On the other hand, some quality attributes such as confidentiality, accessibility, and sustainability are less considered. Also, none of the articles use key-value databases for data storage. This study can help researchers develop more effective BDM in IoT methods in a complex environment. |
format | Online Article Text |
id | pubmed-9664750 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-96647502022-11-14 A comprehensive and systematic literature review on the big data management techniques in the internet of things Naghib, Arezou Jafari Navimipour, Nima Hosseinzadeh, Mehdi Sharifi, Arash Wireless Netw Original Paper The Internet of Things (IoT) is a communication paradigm and a collection of heterogeneous interconnected devices. It produces large-scale distributed, and diverse data called big data. Big Data Management (BDM) in IoT is used for knowledge discovery and intelligent decision-making and is one of the most significant research challenges today. There are several mechanisms and technologies for BDM in IoT. This paper aims to study the important mechanisms in this area systematically. This paper studies articles published between 2016 and August 2022. Initially, 751 articles were identified, but a paper selection process reduced the number of articles to 110 significant studies. Four categories to study BDM mechanisms in IoT include BDM processes, BDM architectures/frameworks, quality attributes, and big data analytics types. Also, this paper represents a detailed comparison of the mechanisms in each category. Finally, the development challenges and open issues of BDM in IoT are discussed. As a result, predictive analysis and classification methods are used in many articles. On the other hand, some quality attributes such as confidentiality, accessibility, and sustainability are less considered. Also, none of the articles use key-value databases for data storage. This study can help researchers develop more effective BDM in IoT methods in a complex environment. Springer US 2022-11-15 2023 /pmc/articles/PMC9664750/ http://dx.doi.org/10.1007/s11276-022-03177-5 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Paper Naghib, Arezou Jafari Navimipour, Nima Hosseinzadeh, Mehdi Sharifi, Arash A comprehensive and systematic literature review on the big data management techniques in the internet of things |
title | A comprehensive and systematic literature review on the big data management techniques in the internet of things |
title_full | A comprehensive and systematic literature review on the big data management techniques in the internet of things |
title_fullStr | A comprehensive and systematic literature review on the big data management techniques in the internet of things |
title_full_unstemmed | A comprehensive and systematic literature review on the big data management techniques in the internet of things |
title_short | A comprehensive and systematic literature review on the big data management techniques in the internet of things |
title_sort | comprehensive and systematic literature review on the big data management techniques in the internet of things |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664750/ http://dx.doi.org/10.1007/s11276-022-03177-5 |
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