期刊
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
卷 138, 期 -, 页码 -出版社
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2019.106564
关键词
Data management; Internet of Things; IoT applications; Big data; Industrial Internet of Things
资金
- FCT - Fundacao para a Ciencia e a Tecnologia [DID/EEA/50008/2019]
- Government of the Russian Federation [08-08]
- Brazilian National Council for Scientific and Technological Development (CNPq) [309335/2017-5]
- Non Linear Analysis, Geometry and Applications Project - Simons Foundation
Internet of Things (IoT) is a network paradigm in which physical, digital, and virtual objects are equipped with identification, detection, networking, and processing functions to communicate with each other and with other devices and services on the Internet in order to perform the users' required tasks. Many IoT applications are provided to bring comfort and facilitate the human life. In addition, the application of IoT technologies in the automotive industry has given rise to the concept of Industrial Internet of Things (IoT) which facilitated using of Cyber Physic Systems, in which machines and humans interact. Due to the diversity, heterogeneity, and large volume of data generated by these entities, the use of traditional database management systems is not suitable in general. In the design of IoT data management systems, many distinctive principles should be considered. These different principles allowed the proposal of several approaches for IoT data management. Some middleware or architecture-oriented solutions facilitate the integration of generated data. Other available solutions provide efficient storage and indexing structured and unstructured data as well as the support to the NoSQL language. Thus, this paper identifies the most relevant concepts of data management in IoT, surveys the current solutions proposed for IoT data management, discusses the most promising solutions, and identifies relevant open research issues on the topic providing guidelines for further contributions. (C) 2019 Elsevier Ltd. All rights reserved.
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