Review of the Complexity of Managing Big Data of the Internet of Things

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Title: Review of the Complexity of Managing Big Data of the Internet of Things
Authors: Gil, David | Johnsson, Magnus | Mora, Higinio | Szymanski, Julian
Research Group/s: Lucentia | Informática Industrial y Redes de Computadores
Center, Department or Service: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Keywords: Complexity | Managing | Big Data | Internet of Things
Knowledge Area: Arquitectura y Tecnología de Computadores
Issue Date: 3-Feb-2019
Publisher: Hindawi Publishing Corporation
Citation: Complexity. 2019. Volume 2019, Article ID 4592902, 12 pages. doi:10.1155/2019/4592902
Abstract: There is a growing awareness that the complexity of managing Big Data is one of the main challenges in the developing field of the Internet of Things (IoT). Complexity arises from several aspects of the Big Data life cycle, such as gathering data, storing them onto cloud servers, cleaning and integrating the data, a process involving the last advances in ontologies, such as Extensible Markup Language (XML) and Resource Description Framework (RDF), and the application of machine learning methods to carry out classifications, predictions, and visualizations. In this review, the state of the art of all the aforementioned aspects of Big Data in the context of the Internet of Things is exposed. The most novel technologies in machine learning, deep learning, and data mining on Big Data are discussed as well. Finally, we also point the reader to the state-of-the-art literature for further in-depth studies, and we present the major trends for the future.
Sponsor: The authors acknowledge the support from the research center Internet of Things and People (IOTAP) at Malmö University in Sweden. This work was also supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under project CloudDriver4Industry TIN2017-89266-R.
URI: http://hdl.handle.net/10045/87650
ISSN: 1076-2787 (Print) | 1099-0526 (Online)
DOI: 10.1155/2019/4592902
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2019 David Gil et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Peer Review: si
Publisher version: https://doi.org/10.1155/2019/4592902
Appears in Collections:INV - LUCENTIA - Artículos de Revistas

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