On Connectivity of Wireless Sensor Networks with Directional Antennas.

Wang, Q; Dai, H-N; Zheng, Z; Imran, M; Vasilakos, AV

On Connectivity of Wireless Sensor Networks with Directional Antennas.

Wang, Q Dai, H-N Zheng, Z Imran, M Vasilakos, AV

Permalink

Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Sensors (Basel), 2017, 17, (1), pp. 1-22
Issue Date:: 2017-01-12

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (885.58 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Wang, Q
dc.contributor.author	Dai, H-N
dc.contributor.author	Zheng, Z
dc.contributor.author	Imran, M
dc.contributor.author	Vasilakos, AV
dc.date.accessioned	2022-08-24T04:41:37Z
dc.date.available	2017-01-05
dc.date.available	2022-08-24T04:41:37Z
dc.date.issued	2017-01-12
dc.identifier.citation	Sensors (Basel), 2017, 17, (1), pp. 1-22
dc.identifier.issn	1424-8220
dc.identifier.issn	1424-8220
dc.identifier.uri	http://hdl.handle.net/10453/160787
dc.description.abstract	In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.
dc.format	Electronic
dc.language	eng
dc.publisher	MDPI
dc.relation.ispartof	Sensors (Basel)
dc.relation.isbasedon	10.3390/s17010134
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0301 Analytical Chemistry, 0502 Environmental Science and Management, 0602 Ecology, 0805 Distributed Computing, 0906 Electrical and Electronic Engineering
dc.subject.classification	Analytical Chemistry
dc.title	On Connectivity of Wireless Sensor Networks with Directional Antennas.
dc.type	Journal Article
utslib.citation.volume	17
utslib.location.activity	Switzerland
utslib.for	0301 Analytical Chemistry
utslib.for	0502 Environmental Science and Management
utslib.for	0602 Ecology
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
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.consider-herdc	false
dc.date.updated	2022-08-24T04:41:28Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	17
utslib.citation.issue	1

Abstract:

In this paper, we investigate the network connectivity of wireless sensor networks with directional antennas. In particular, we establish a general framework to analyze the network connectivity while considering various antenna models and the channel randomness. Since existing directional antenna models have their pros and cons in the accuracy of reflecting realistic antennas and the computational complexity, we propose a new analytical directional antenna model called the iris model to balance the accuracy against the complexity. We conduct extensive simulations to evaluate the analytical framework. Our results show that our proposed analytical model on the network connectivity is accurate, and our iris antenna model can provide a better approximation to realistic directional antennas than other existing antenna models.

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

http://hdl.handle.net/10453/160787