Kuiper test and autoregressive model-based approach for wireless sensor network fault diagnosis

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

40 Scopus Citations
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Author(s)

  • Xiaohang Jin
  • Tommy W. S. Chow
  • Yi Sun
  • Jihong Shan
  • Bill C. P. Lau

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)829-839
Journal / PublicationWireless Networks
Volume21
Issue number3
Online published27 Sept 2014
Publication statusPublished - Apr 2015

Abstract

Wireless sensor networks (WSNs) have recently received increasing attention in the areas of defense and civil applications of sensor networks. Automatic WSN fault detection and diagnosis is essential to assure system’s reliability. Proactive WSNs fault diagnosis approaches use embedded functions scanning sensor node periodically for monitoring the health condition of WSNs. But this approach may speed up the depletion of limited energy in each sensor node. Thus, there is an increasing interest in using passive diagnosis approach. In this paper, WSN anomaly detection model based on autoregressive (AR) model and Kuiper test-based passive diagnosis is proposed. First, AR model with optimal order is developed based on the normal working condition of WSNs using Akaike information criterion. The AR model then acts as a filter to process the future incoming signal from different unknown conditions. A health indicator based on Kuiper test, which is used to test the similarity between the training error of normal condition and residual of test conditions, is derived for indicating the health conditions of WSN. In this study, synthetic WSNs data under different cases/conditions were generated and used for validating the approach. Experimental results show that the proposed approach could differentiate WSNs normal conditions from faulty conditions. At last, the overall results presented in this paper demonstrate that our approach is effective for performing WSNs anomalies detection.

Research Area(s)

  • Anomaly detection, Autoregressive model, Kuiper test, Wireless sensor network

Citation Format(s)

Kuiper test and autoregressive model-based approach for wireless sensor network fault diagnosis. / Jin, Xiaohang; Chow, Tommy W. S.; Sun, Yi et al.
In: Wireless Networks, Vol. 21, No. 3, 04.2015, p. 829-839.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review