Adaptive consensus-based aggregation for edge computing

Al-Doghman, F; Chaczko, Z; Brookes, W

Adaptive consensus-based aggregation for edge computing

Al-Doghman, F

Chaczko, Z

Brookes, W

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Publication Type:: Conference Proceeding
Citation:: 26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings, 2019
Issue Date:: 2019-02-08

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Field	Value	Language
dc.contributor.author	Al-Doghman, F https://orcid.org/0000-0002-1020-8097	en_US
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Brookes, W https://orcid.org/0000-0002-6524-1126	en_US
dc.date.issued	2019-02-08	en_US
dc.identifier.citation	26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings, 2019	en_US
dc.identifier.isbn	9781538678343	en_US
dc.identifier.uri	http://hdl.handle.net/10453/130406
dc.description.abstract	© 2018 IEEE. The swift expansion in employing IoT and the tendency to apply its application have encompassed a wide range of fields in our life. The heterogeneity and the massive amount of data produced from IoT require adaptive collection and transmission processes that function closed to front-end to mitigate these issues. In this paper, We introduced a method of aggregating IoT data in a consensus way using Bayesian analysis and Markov Chain techniques. The aim is to enhance the quality of data traveling within IoT framework.	en_US
dc.relation.ispartof	26th International Conference on Systems Engineering, ICSEng 2018 - Proceedings	en_US
dc.relation.isbasedon	10.1109/ICSENG.2018.8638200	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Adaptive consensus-based aggregation for edge computing	en_US
dc.type	Conference Proceeding
utslib.for	0804 Data Format	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Teaching and Learning)
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
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access	*
pubs.publication-status	Published	en_US

Abstract:

© 2018 IEEE. The swift expansion in employing IoT and the tendency to apply its application have encompassed a wide range of fields in our life. The heterogeneity and the massive amount of data produced from IoT require adaptive collection and transmission processes that function closed to front-end to mitigate these issues. In this paper, We introduced a method of aggregating IoT data in a consensus way using Bayesian analysis and Markov Chain techniques. The aim is to enhance the quality of data traveling within IoT framework.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/130406