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Faulty Data Detection in Wireless Sensor Networks Based on Copula Theory

Farid Lalem 1 Ahcène Bounceur 1 Rahim Kacimi 2 Reinhardt Euler 1 Saoudi Massinissa 1
1 Lab-STICC_UBO_CACS_MOCS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
2 IRIT-T2RS - Temps Réel dans les Réseaux et Systèmes
IRIT - Institut de recherche en informatique de Toulouse
Abstract : Wireless Sensor Networks (WSNs) are a powerful instrument for monitoring and recording physical phenomena. Very often the quality of the sensed data collected by sensor nodes is affected by noise and errors, events, and malicious attacks. Also, the processing and the transmitting of this data over the network may drain the amount of available resources of WSNs and decrease rapidly the network lifetime. Therefore, there is an urgent need to detect faulty data in order to insure the reliability of data and keep the resource of WSNs at a high level. In this paper, we propose a new approach for faulty data detection in WSNs based on Copula theory. Our experimental results on real data sets collected by real sensor networks show that a significant percentage of the data are faulty.
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https://hal.univ-brest.fr/hal-01397975
Contributor : Ahcène Bounceur Connect in order to contact the contributor
Submitted on : Wednesday, November 16, 2016 - 2:59:07 PM
Last modification on : Tuesday, October 19, 2021 - 2:24:13 PM

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Farid Lalem, Ahcène Bounceur, Rahim Kacimi, Reinhardt Euler, Saoudi Massinissa. Faulty Data Detection in Wireless Sensor Networks Based on Copula Theory. International conference on Big Data and Advanced Wireless technologies (BDAW 2016), Nov 2016, Blagoevgrad, Bulgaria. ⟨10.1145/3010089.3010114⟩. ⟨hal-01397975⟩

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