- Title
- On connectivity of wireless sensor networks with directional antennas
- Creator
- Wang, Qiu; Dai, Hong-Ning; Zheng, Zibin; Imran, Muhammad; Vasilakos, Athanasios
- Date
- 2017
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/186134
- Identifier
- vital:16835
- Identifier
-
https://doi.org/10.3390/s17010134
- Identifier
- ISBN:1424-8220 (ISSN)
- 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. © 2017 by the authors; licensee MDPI, Basel, Switzerland.
- Publisher
- MDPI AG
- Relation
- Sensors (Switzerland) Vol. 17, no. 1 (2017), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright @ 2017 by the authors
- Rights
- Open Access
- Subject
- 4008 Electrical engineering; 4009 Electronics, sensors and digital hardware; 4606 Distributed computing and systems software; Connectivity; Directional antennas; Wireless sensor networks
- Full Text
- Reviewed
- Funder
- The work described in this paper was supported by Macao Science and Technology Development Fund under Grant No. 096/2013/A3, National Key Research and Development Program (2016YFB1000101) and the National Natural Science Foundation of China (61472338). The authors extend their appreciation to the International Scientific Partnership Program ISPP at King Saud University for funding this research work through ISPP# 0033.
- Hits: 702
- Visitors: 575
- Downloads: 62
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Published version | 885 KB | Adobe Acrobat PDF | View Details Download |