Enhancing Crowd Collaborations for Software Defined Vehicular Networks

Quan, W; Liu, Y; Zhang, H; Yu, S

Enhancing Crowd Collaborations for Software Defined Vehicular Networks

Quan, W Liu, Y Zhang, H Yu, S

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Communications Magazine, 2017, 55, (8), pp. 80-86
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Quan, W
dc.contributor.author	Liu, Y
dc.contributor.author	Zhang, H
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2022-08-16T05:01:02Z
dc.date.available	2022-08-16T05:01:02Z
dc.date.issued	2017-01-01
dc.identifier.citation	IEEE Communications Magazine, 2017, 55, (8), pp. 80-86
dc.identifier.issn	0163-6804
dc.identifier.issn	1558-1896
dc.identifier.uri	http://hdl.handle.net/10453/160337
dc.description.abstract	Vehicular networking is promising to improve traffic efficiency and driving safety, as well as travel experience. However, the traditional network employs a highly coupled design, which is quite limited in its ability to satisfy various challenging vehicular demands. Recently, new studies focus on how to design software defined vehicular networks smartly to meet various vehicular demands. In this article, we investigate a new smart identifier networking (SINET) paradigm and propose a SINET customized solution enabling crowd collaborations for software defined vehicular networks (SINET-V). In particular, through crowd sensing, network function slices are well organized with a group of function-similar components. Different function slices are further driven to serve various applications by using crowd collaborations. We clearly illustrate how SINET-V works and also analyze its potential advantages in several special vehicular instances. Experimental results show that SINET-V has great potential to promote powerful vehicular networks.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Communications Magazine
dc.relation.isbasedon	10.1109/MCOM.2017.1601162
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.title	Enhancing Crowd Collaborations for Software Defined Vehicular Networks
dc.type	Journal Article
utslib.citation.volume	55
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
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 Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-08-16T05:01:00Z
pubs.issue	8
pubs.publication-status	Published
pubs.volume	55
utslib.citation.issue	8

Abstract:

Vehicular networking is promising to improve traffic efficiency and driving safety, as well as travel experience. However, the traditional network employs a highly coupled design, which is quite limited in its ability to satisfy various challenging vehicular demands. Recently, new studies focus on how to design software defined vehicular networks smartly to meet various vehicular demands. In this article, we investigate a new smart identifier networking (SINET) paradigm and propose a SINET customized solution enabling crowd collaborations for software defined vehicular networks (SINET-V). In particular, through crowd sensing, network function slices are well organized with a group of function-similar components. Different function slices are further driven to serve various applications by using crowd collaborations. We clearly illustrate how SINET-V works and also analyze its potential advantages in several special vehicular instances. Experimental results show that SINET-V has great potential to promote powerful vehicular networks.

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

http://hdl.handle.net/10453/160337