Enabling Design of Middleware for Massive Scale IOT-based Systems

Chaczko, Z; Klempous, R; Rozenblit, J; Chiu, C; Kluwak, K; Smutnicki, C

Enabling Design of Middleware for Massive Scale IOT-based Systems

Chaczko, Z

Klempous, R Rozenblit, J Chiu, C

Kluwak, K Smutnicki, C

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Publication Type:: Conference Proceeding
Citation:: 2019
Issue Date:: 2019-04-26

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Field	Value	Language
dc.contributor.author	Chaczko, Z https://orcid.org/0000-0002-2816-7510	en_US
dc.contributor.author	Klempous, R	en_US
dc.contributor.author	Rozenblit, J	en_US
dc.contributor.author	Chiu, C https://orcid.org/0000-0003-2045-5961	en_US
dc.contributor.author	Kluwak, K	en_US
dc.contributor.author	Smutnicki, C	en_US
dc.date	2019-04-25	en_US
dc.date.available	2021-04-27T19:00:47Z
dc.date.issued	2019-04-26	en_US
dc.identifier.citation	2019	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137553
dc.description.abstract	Recently, the Internet of Things (IoT) technology has rapidly advanced to the stage where it is feasible to discover, locate and identify various smart sensors and devices based on the context, situation, characteristics, and relevancy to query for their data or control actions. Taking things a step further when developing Large Scale Applications requires that two serious issues be overcome. The first issue is to find a solution for data sensing and collection from a massive number of various ubiquitous devices when converging these into the next generation networks. The second important issue is to deal with the “Big Data” that arrive from a very large number of sources. This research emphasizes the need for finding a solution for a large scale data aggregation and delivery. The paper introduces biomimetic design methods for data aggregation in the context of large scale IoT-based systems.	en_US
dc.relation.ispartof	23rd IEEE International Conference on Intelligent Engineering Systems 2019	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Enabling Design of Middleware for Massive Scale IOT-based Systems	en_US
dc.type	Conference Proceeding
utslib.location	Gödöllő, Hungary	en_US
utslib.location.activity	Gödöllő, Hungary	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 Design, Architecture and Building
pubs.organisational-group	/University of Technology Sydney/Faculty of Design, Architecture and Building/School of Architecture
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	open_access	*
pubs.consider-herdc	true	en_US
pubs.finish-date	2019-04-26	en_US
pubs.place-of-publication	Gödöllő, Hungary	en_US
pubs.start-date	2019-04-25	en_US

Abstract:

Recently, the Internet of Things (IoT) technology has rapidly advanced to the stage where it is feasible to discover, locate and identify various smart sensors and devices based on the context, situation, characteristics, and relevancy to query for their data or control actions. Taking things a step further when developing Large Scale Applications requires that two serious issues be overcome. The first issue is to find a solution for data sensing and collection from a massive number of various ubiquitous devices when converging these into the next generation networks. The second important issue is to deal with the “Big Data” that arrive from a very large number of sources. This research emphasizes the need for finding a solution for a large scale data aggregation and delivery. The paper introduces biomimetic design methods for data aggregation in the context of large scale IoT-based systems.

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http://hdl.handle.net/10453/137553