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Sensors 2016, 16(7), 960; doi:10.3390/s16070960

DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks

1
Department of Electrical Engineering and Computer Science, University of Applied Sciences of Münster, Stegerwaldstr. 39, D-48565 Steinfurt, Germany
2
Department of Computer Architecture and Technology, University of Granada, Periodista Daniel Saucedo Aranda, S/N, 18071 Granada, Spain
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Ignacio Bravo
Received: 16 March 2016 / Revised: 23 May 2016 / Accepted: 15 June 2016 / Published: 24 June 2016
(This article belongs to the Special Issue Trusted and Secure Wireless Sensor Network Designs and Deployments)
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Abstract

The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities. View Full-Text
Keywords: network routing algorithm; WSN; Smart City; RPL; AODV; IEEE 802.15.4 network routing algorithm; WSN; Smart City; RPL; AODV; IEEE 802.15.4
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MDPI and ACS Style

Estévez, F.J.; Glösekötter, P.; González, J. DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks. Sensors 2016, 16, 960.

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