A Big Data Analytics Architecture For The Internet Of Small Things
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.
Publication Date
2-1-2018
Publication Title
IEEE Communications Magazine
Volume
56
Issue
2
Number of Pages
128-133
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/MCOM.2018.1700273
Copyright Status
Unknown
Socpus ID
85042178500 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85042178500
STARS Citation
Gohar, Moneeb; Ahmed, Syed Hassan; Khan, Murad; Guizani, Nadra; and Ahmed, Awais, "A Big Data Analytics Architecture For The Internet Of Small Things" (2018). Scopus Export 2015-2019. 8623.
https://stars.library.ucf.edu/scopus2015/8623