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Open AccessArticle

On Connectivity of Wireless Sensor Networks with Directional Antennas

1
Faculty of Information Technology, Macau University of Science and Technology, Macau, China
2
School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510006, China
3
College of Computer and Information Sciences, King Saud University, Riyadh 12372, Saudi Arabia
4
Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, Luleå 971 87, Sweden
*
Author to whom correspondence should be addressed.
Academic Editors: Giancarlo Fortino, Hassan Ghasemzadeh, Wenfeng Li, Yin Zhang and Luca Benini
Sensors 2017, 17(1), 134; https://doi.org/10.3390/s17010134
Received: 6 November 2016 / Revised: 28 December 2016 / Accepted: 5 January 2017 / Published: 12 January 2017
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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. View Full-Text
Keywords: connectivity; wireless sensor networks; directional antennas connectivity; wireless sensor networks; directional antennas
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MDPI and ACS Style

Wang, Q.; Dai, H.-N.; Zheng, Z.; Imran, M.; Vasilakos, A.V. On Connectivity of Wireless Sensor Networks with Directional Antennas. Sensors 2017, 17, 134.

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