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QoS-Aware Fault Detection in Wireless Sensor Networks

De Paola, Alessandra; Lo Re, Giuseppe; Milazzo, Fabrizio; Ortolani, Marco

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Authors

Alessandra De Paola

Giuseppe Lo Re

Fabrizio Milazzo



Abstract

Wireless sensor networks (WSNs) are a fundamental building block of many pervasive applications. Nevertheless the use of such technology raises new challenges regarding the development of reliable and fault-tolerant systems. One of the most critical issues is the detection of corrupted readings amidst the huge amount of gathered sensory data. Indeed, such readings could significantly affect the quality of service (QoS) of the WSN, and thus it is highly desirable to automatically discard them. This issue is usually addressed through “fault detection” algorithms that classify readings by exploiting temporal and spatial correlations. Generally, these algorithms do not take into account QoS requirements other than the classification accuracy. This paper proposes a fully distributed algorithm for detecting data faults, taking into account the response time besides the classification accuracy. We adopt the Bayesian networks to perform classification of readings and the Pareto optimization to allow QoS requirements to be simultaneously satisfied. Our approach has been tested on a synthetic dataset in order to evaluate its behavior with respect to different values of QoS constraints. The experimental evaluation produced good results, showing that our algorithm is able to greatly reduce the response time at the cost of a small reduction in classification accuracy.

Citation

De Paola, A., Lo Re, G., Milazzo, F., & Ortolani, M. (2013). QoS-Aware Fault Detection in Wireless Sensor Networks. International Journal of Distributed Sensor Networks, https://doi.org/10.1155/2013/165732

Journal Article Type Article
Acceptance Date Jul 28, 2013
Online Publication Date Sep 12, 2013
Publication Date Sep 1, 2013
Journal International Journal of Distributed Sensor Networks
Print ISSN 1550-1329
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1155/2013/165732
Publisher URL https://journals.sagepub.com/doi/full/10.1155/2013/165732

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