D 2018

Exploring Big Data Clustering Algorithms for Internet of Things Applications

BANGUI, Hind, Mouzhi GE and Barbora BÜHNOVÁ

Basic 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

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
Name: CERIT Scientific Cloud