Big data analytics for large-scale wireless networks: Challenges and opportunities

Dai, HN; Wong, RCW; Wang, H; Zheng, Z; Vasilakos, AV

Big data analytics for large-scale wireless networks: Challenges and opportunities

Dai, HN Wong, RCW Wang, H Zheng, Z Vasilakos, AV

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Publication Type:: Journal Article
Citation:: ACM Computing Surveys, 2019, 52 (5)
Issue Date:: 2019-09-01

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Field	Value	Language
dc.contributor.author	Dai, HN	en_US
dc.contributor.author	Wong, RCW	en_US
dc.contributor.author	Wang, H	en_US
dc.contributor.author	Zheng, Z	en_US
dc.contributor.author	Vasilakos, AV https://orcid.org/0000-0003-1902-9877	en_US
dc.date.issued	2019-09-01	en_US
dc.identifier.citation	ACM Computing Surveys, 2019, 52 (5)	en_US
dc.identifier.issn	0360-0300	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137545
dc.description.abstract	© 2019 Association for Computing Machinery. The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large-scale wireless networks. Big data of large-scale wireless networks has the key features of wide variety, high volume, real-time velocity, and huge value leading to the unique research challenges that are different from existing computing systems. In this article, we present a survey of the state-of-art big data analytics (BDA) approaches for large-scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage, and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large-scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area.	en_US
dc.relation.ispartof	ACM Computing Surveys	en_US
dc.relation.isbasedon	10.1145/3337065	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Information Systems	en_US
dc.title	Big data analytics for large-scale wireless networks: Challenges and opportunities	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.citation.volume	52	en_US
utslib.for	0805 Distributed Computing	en_US
utslib.for	08 Information and Computing Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	52	en_US

Abstract:

© 2019 Association for Computing Machinery. The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large-scale wireless networks. Big data of large-scale wireless networks has the key features of wide variety, high volume, real-time velocity, and huge value leading to the unique research challenges that are different from existing computing systems. In this article, we present a survey of the state-of-art big data analytics (BDA) approaches for large-scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage, and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large-scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area.

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http://hdl.handle.net/10453/137545