A generic data management framework for the internet of things
Núñez Sánchez, Diego Fernando
Cantor, Juan Sebastián
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By 2025, it is estimated that there will be over 75 billion devices connected to the Internet, and it is expected that data volumes will continue to grow exponentially. As such, there will be an increasing need for e ective data management of data generated by sensors in the Internet of Things (IoT). In this paper, we propose a lightweight, generic data processing framework that may be easily customized for a diverse range of data-handling IoT applications. The sensor types required by an application are speci ed as metadata. Sensed data is persistently stored in a horizontally partitioned relational database across IoT nodes. Subsequently, it may be retrieved by posing SQL queries over the nodes, which may be historical or real-time. Alternatively, the sensed data may also be retrieved as a JSON document over a RESTful interface, thus potentially enabling easier integration with cloud and mobile platforms. We show an instantiation of the framework for applications in the climate monitoring and security domains.
Link to resourcehttps://www.semanticscholar.org/paper/A-Generic-Data-Management-Framework-for-the-of-Núñez-Sánchez-Cantor/082e1753a3b62ce29bb2b4391bbf9f7129c481f3
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