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Sensors 2015, 15(11), 27436-27469;

SITRUS: Semantic Infrastructure for Wireless Sensor Networks

Department of Computer Science (DCOMP), Federal University of Sergipe (UFS), Aracaju, SE 49100-000, Brazil
Centre of Informatics (CIn), Federal University of Pernambuco (UFPE), Recife, PE 50740-560, Brazil
Author to whom correspondence should be addressed.
Academic Editor: Davide Brunelli
Received: 4 June 2015 / Revised: 13 October 2015 / Accepted: 19 October 2015 / Published: 29 October 2015
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Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks), which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS. View Full-Text
Keywords: semantic infrastructure; wireless sensor networks; ontology and semantic web; power consumption; software reconfiguration semantic infrastructure; wireless sensor networks; ontology and semantic web; power consumption; software reconfiguration

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Bispo, K.A.; Rosa, N.S.; Cunha, P.R.F. SITRUS: Semantic Infrastructure for Wireless Sensor Networks. Sensors 2015, 15, 27436-27469.

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