Streaming Analysis in Wireless Sensor Networks

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Moshtaghi, Masud; Bezdek, James C.; Havens, Timothy C.; Leckie, Chris; Karunasekera, Shanika; Rajasegarar, Sutharshan; Palaniswami, Marimuthu


2012-08-01


Journal Article


Wireless Communications & Mobile Computing


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Two new incremental models for on-line anomaly detection in data streams at nodes in wireless sensor networks (WSNs) are discussed. These models are incremental versions of a model that uses ellipsoids to detect first, second and higher ordered anomalies in arrears. The incremental versions can also be used this way, but have additional capabilities offered by processing data incrementally as they arrive in time. Specifically, they can detect anomalies "on-the-fly" in near real time. They can also be used to track temporal changes in near real-time due to sensor drift, cyclic variation, or seasonal changes. One of the new models has a mechanism that enables graceful degradation of inputs in the distant past (fading memory). Three real data sets from single sensors in deployed environmental monitoring networks are used to illustrate various facets of the new models. Examples compare the incremental version to previous batch and dynamic models, and show that the incremental versions can detect various types of dynamic anomalies in near real time.


Anomaly Detection, Environmental Monitoring, Temporal Chains, Temporal data, Wireless Sensor Networks


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nicta:5196


Moshtaghi, Masud; Bezdek, James C.; Havens, Timothy C.; Leckie, Chris; Karunasekera, Shanika; Rajasegarar, Sutharshan; Palaniswami, Marimuthu. Streaming Analysis in Wireless Sensor Networks. Wireless Communications &amp; Mobile Computing. 2012-08-01; TBA(TBA):TBA. <a href="http://hdl.handle.net/102.100.100/99936?index=1" target="_blank">http://hdl.handle.net/102.100.100/99936?index=1</a>



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