A Big Data Analytics Architecture for the Internet of Small Things
Document Type
Article
Publication Date
2-1-2018
Publication Title
IEEE Communications Magazine
DOI
10.1109/MCOM.2018.1700273
ISSN
1558-1896
Abstract
The SK Telecom Company of South Korea recently introduced the concept of IoST to its business model. The company deployed IoST, which constantly generates data via the LoRa wireless platform. The increase in data rates generated by IoST is escalating exponentially. After attempting to analyze and store the massive volume of IoST data using existing tools and technologies, the South Korean company realized the shortcomings immediately. The current article addresses some of the issues and presents a big data analytics architecture for its IoST. A system developed using the proposed architecture will be able to analyze and store IoST data efficiently while enabling better decisions. The proposed architecture is composed of four layers, namely the small things layer, infrastructure layer, platform layer, and application layer. Finally, a detailed analysis of a big data implementation of the IoST used to track humidity and temperature via Hadoop is presented as a proof of concept.
Recommended Citation
Gohar, Moneeb, Syed Hassan Ahmed, Murad Khan, Nadra Guizani, Awais Ahmed, Arif Ur Rahman.
2018.
"A Big Data Analytics Architecture for the Internet of Small Things."
IEEE Communications Magazine, 56 (2): 128-133.
doi: 10.1109/MCOM.2018.1700273
https://digitalcommons.georgiasouthern.edu/compsci-facpubs/170