A Research Roadmap of Big Data Clustering Algorithms for Future Internet of Things

BANGUI, Hind, Mouzhi GE and Barbora BÜHNOVÁ. A Research Roadmap of Big Data Clustering Algorithms for Future Internet of Things. International Journal of Organizational and Collective Intelligence. IGI, vol. 9, No 2, p. 16-30. ISSN 1947-9344. doi:10.4018/IJOCI.2019040102. 2019.

Basic information

• Original name: A Research Roadmap of Big Data Clustering Algorithms for Future Internet of Things
• Authors: BANGUI, Hind (504 Morocco, belonging to the institution), Mouzhi GE (156 China, guarantor, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution).
• Edition: International Journal of Organizational and Collective Intelligence, IGI, 2019, 1947-9344.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: United States of America
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• RIV identification code: RIV/00216224:14610/19:00108886
• Organization unit: Institute of Computer Science
• Doi: http://dx.doi.org/10.4018/IJOCI.2019040102
• Keywords in English: Big Data; Internet of Things; Clustering Algorithm; Machine Learning; Mobile Networks
• Tags: rivok
• Tags: International impact, Reviewed

Abstract

Due to the massive data increase in different Internet of Things (IoT) domains such as healthcare IoT and Smart City IoT, Big Data technologies have been emerged as critical analytics tools for analyzing the IoT data. Among the Big Data technologies, data clustering is one of the essential approaches to process the IoT data. However, how to select a suitable clustering algorithm for IoT data is still unclear. Furthermore, since Big Data technology are still in its initial stage for different IoT domains, it is thus valuable to propose and structure the research challenges between Big Data and IoT. Therefore, this paper starts from reviewing and comparing the data clustering algorithms that can be applied in IoT datasets, and then extends the discussions to a broader IoT context such as IoT dynamics and IoT mobile networks. Finally, this paper identifies a set of research challenges that harvest a research roadmap for the Big Data research in IoT domains. The proposed research roadmap aims at bridging the research gaps between Big Data and various IoT contexts.

Links

• EF16_013/0001802, research and development project: Name: CERIT Scientific Cloud