Detailed Information on Publication Record
2018
Exploring Big Data Clustering Algorithms for Internet of Things Applications
BANGUI, Hind, Mouzhi GE and Barbora BÜHNOVÁBasic information
Original name
Exploring Big Data Clustering Algorithms for Internet of Things Applications
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
Madeira, Portugal, Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security, p. 269-276, 8 pp. 2018
Publisher
SCITEPRESS
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10200 1.2 Computer and information sciences
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
References:
RIV identification code
RIV/00216224:14610/18:00102285
Organization unit
Institute of Computer Science
ISBN
978-989-758-296-7
Keywords in English
Big Data; Internet of Things; Clustering Algorithm; Machine Learning; Mobile Networks
Tags
International impact, Reviewed
Změněno: 20/3/2019 15:03, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
With the rapid development of the Big Data and Internet of Things (IoT), Big Data technologies have emerged as a key data analytics tool in IoT, in which, data clustering algorithms are considered as an essential component for data analysis. However, there has been limited research that addresses the challenges across Big Data and IoT and thus proposing a research agenda is important to clarify the research challenges for clustering Big Data in the context of IoT. By tackling this specific aspect - clustering algorithm in Big Data, this paper examines on Big Data technologies, related data clustering algorithms and possible usages in IoT. Based on our review, this paper identifies a set of research challenges that can be used as a research agenda for the Big Data clustering research. This research agenda aims at identifying and bridging the research gaps between Big Data clustering algorithms and IoT.
Links
EF16_013/0001802, research and development project |
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