A holistic approach to a context-aware IoT ecosystem with Adaptive Ubiquitous Middleware

Pradeep, P; Krishnamoorthy, S; Vasilakos, AV

A holistic approach to a context-aware IoT ecosystem with Adaptive Ubiquitous Middleware

Pradeep, P Krishnamoorthy, S Vasilakos, AV

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Pervasive and Mobile Computing, 2021, 72
Issue Date:: 2021-04-01

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Field	Value	Language
dc.contributor.author	Pradeep, P
dc.contributor.author	Krishnamoorthy, S
dc.contributor.author	Vasilakos, AV
dc.date.accessioned	2022-02-22T22:52:38Z
dc.date.available	2022-02-22T22:52:38Z
dc.date.issued	2021-04-01
dc.identifier.citation	Pervasive and Mobile Computing, 2021, 72
dc.identifier.issn	1574-1192
dc.identifier.issn	1873-1589
dc.identifier.uri	http://hdl.handle.net/10453/154787
dc.description.abstract	The Internet of Things is envisioned to provide connectivity and communication between various devices all over the world. Based on the devices and applications involved, the nature of the network formed differs. Thus, an intelligent and holistic ecosystem needs to be created wherein clients, data sources, smart objects, and services can all co-exist and interact with each other. We present Adaptive Ubiquitous Middleware for context-aware IoT ecosystems, which considers the situational context of the applications, devices, or people and the contexts of the network formed and accordingly adapts the behavior of the ecosystem. Adaptive Ubiquitous Middleware is a multi-agent, multi-communication protocol-facilitated middleware that acts as an integration point for applications to access relevant context, share it with other applications, and have relevant services made available via a multi-communication protocol bridge. We also present an optimal service allocation model for a single service class that utilizes available computing resources and achieves a minimum average response time. The system implementation has been evaluated with two use cases to demonstrate its applicability, effectiveness, and generality. The evaluation of optimal service allocation demonstrates the service response is much faster in the proposed model.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Pervasive and Mobile Computing
dc.relation.isbasedon	10.1016/j.pmcj.2021.101342
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0805 Distributed Computing, 1702 Cognitive Sciences
dc.subject.classification	Networking & Telecommunications
dc.title	A holistic approach to a context-aware IoT ecosystem with Adaptive Ubiquitous Middleware
dc.type	Journal Article
utslib.citation.volume	72
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0805 Distributed Computing
utslib.for	1702 Cognitive Sciences
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	closed_access	*
dc.date.updated	2022-02-22T22:52:36Z
pubs.publication-status	Published
pubs.volume	72

Abstract:

The Internet of Things is envisioned to provide connectivity and communication between various devices all over the world. Based on the devices and applications involved, the nature of the network formed differs. Thus, an intelligent and holistic ecosystem needs to be created wherein clients, data sources, smart objects, and services can all co-exist and interact with each other. We present Adaptive Ubiquitous Middleware for context-aware IoT ecosystems, which considers the situational context of the applications, devices, or people and the contexts of the network formed and accordingly adapts the behavior of the ecosystem. Adaptive Ubiquitous Middleware is a multi-agent, multi-communication protocol-facilitated middleware that acts as an integration point for applications to access relevant context, share it with other applications, and have relevant services made available via a multi-communication protocol bridge. We also present an optimal service allocation model for a single service class that utilizes available computing resources and achieves a minimum average response time. The system implementation has been evaluated with two use cases to demonstrate its applicability, effectiveness, and generality. The evaluation of optimal service allocation demonstrates the service response is much faster in the proposed model.

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http://hdl.handle.net/10453/154787