Abstract
Over the last few years, wireless sensor networks (WSNs) have attracted tangible involvement particularly in the field of surveillance and monitoring works. Usually the data measured by the sensor nodes is contaminated with noise and this data which is deviated very much from its normal behavior is called as outlier or abnormal data. This paper puts forward outlier detection by cluster head based on spatial correlation approach. The performance of the proposed algorithm is evaluated using simulation in terms of detection accuracy (DA) and false alarm rate (FAR). It is also compared with existing DODCF algorithm. Improvements have been observed in the proposed algorithm in terms of DA, FAR, and message complexity.
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Kamboj, R., Gupta, V. (2020). Spatial Correlation Based Outlier Detection in Clustered Wireless Sensor Network. In: Singh Tomar, G., Chaudhari, N.S., Barbosa, J.L.V., Aghwariya, M.K. (eds) International Conference on Intelligent Computing and Smart Communication 2019. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0633-8_13
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DOI: https://doi.org/10.1007/978-981-15-0633-8_13
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