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Wireless Personal Communications

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15-06-2017

Outlier Detection in Wireless Sensor Networks Based on OPTICS Method for Events and Errors Identification

Authors: Aymen Abid, Atef Masmoudi, Abdennaceur Kachouri, Adel Mahfoudhi

Published in: Wireless Personal Communications | Issue 1/2017

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Abstract

Wireless Sensor Network is composed of small, low cost, low energy, and multifunctional sensors. In addition, this network could have scalability, topology, synchronization, radio-coverage, safety and security constraints . Therefore, our challenge is to classify data into normal and abnormal measurements using outlier detection methods. This paper explore the density-based method Ordering Points to Identify the Clustering Structure. Proposed detector applies an auto- configuration of parameters without previous known environmental conditions. It also extracts hierarchical clusters that serve in a post-processing treatment for classification of data into errors and events. Performance is examined within a real and synthetic databases from Intel Berkeley Research lab. Results demonstrate that our proposed process analyzes data of this network with an average equal to 81% of outlier detection rate, 74% of precision rate and only 2% of false alarms rate that it is very low compared to other methods.

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Title: Outlier Detection in Wireless Sensor Networks Based on OPTICS Method for Events and Errors Identification
Authors: Aymen Abid
Atef Masmoudi
Abdennaceur Kachouri
Adel Mahfoudhi
Publication date: 15-06-2017
Publisher: Springer US
Published in: Wireless Personal Communications / Issue 1/2017
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-017-4583-7

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