Exploring Big Data Clustering Algorithms for Internet of Things Applications

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Publikace nespadá pod Fakultu sportovních studií, ale pod Ústav výpočetní techniky. Oficiální stránka publikace je na webu muni.cz.
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BANGUI Hind GE Mouzhi BÜHNOVÁ Barbora

Rok publikování 2018
Druh Článek ve sborníku
Konference Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security
Fakulta / Pracoviště MU

Ústav výpočetní techniky

Citace
www http://www.scitepress.org/PublicationsDetail.aspx?ID=Frf7G1jpPY4=&t=1
Doi http://dx.doi.org/10.5220/0006773402690276
Klíčová slova Big Data; Internet of Things; Clustering Algorithm; Machine Learning; Mobile Networks
Popis 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.
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