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A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks

1
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
2
School of Computing and Communications, University of Technology Sydney, Sydney 2109, Australia
3
Faculty of Engineering and Computing, Coventry University, Coventry CV1 5FB, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Sensors 2016, 16(7), 1108; https://doi.org/10.3390/s16071108
Received: 15 June 2016 / Revised: 7 July 2016 / Accepted: 11 July 2016 / Published: 18 July 2016
(This article belongs to the Section Sensor Networks)
Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled. View Full-Text
Keywords: medium access control; carrier sensing range; data collection; wireless sensor network medium access control; carrier sensing range; data collection; wireless sensor network
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Lei, C.; Bie, H.; Fang, G.; Gaura, E.; Brusey, J.; Zhang, X.; Dutkiewicz, E. A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks. Sensors 2016, 16, 1108.

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