A hybrid fault detection approach for context-aware wireless sensor networks

Ehsan Ullah Warriach, Tuan Anh Nguyen, Marco Aiello, Kenji Tei

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

Wireless Sensor Network (WSN) deployment experiences show that data collected is prone to be imprecise and faulty due to internal and external influences, such as battery drain, environmental interference, sensor aging. An early detection of such faults is necessary for the effective operation of the sensor network. We focus on identifying data fault types and their causes. In particular, we propose a hybrid approach to the detection of faults based on three qualitatively different classes of fault detection methods. Rule-based methods leverage domain and expert knowledge to develop heuristic rules for identifying and classifying faults. Estimation methods predict normal sensor behavior by leveraging sensor spatial and temporal correlations, identifying erroneous sensor readings as faults. Finally, learning-based methods are inferred a model for the faulty sensor readings using training data and statistically detect and identify classes of faults. We illustrate the performance of a hybrid approach on data coming from two actual sensor deployments.

本文言語English
ホスト出版物のタイトルMASS 2012 - 9th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems
ページ281-289
ページ数9
DOI
出版ステータスPublished - 2012 12 1
外部発表はい
イベント9th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2012 - Las Vegas, NV, United States
継続期間: 2012 10 82012 10 11

出版物シリーズ

名前MASS 2012 - 9th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems

Other

Other9th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, MASS 2012
CountryUnited States
CityLas Vegas, NV
Period12/10/812/10/11

ASJC Scopus subject areas

  • Computer Networks and Communications

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