Abstract
Recent years of research on sensor networks have resulted in multi-scale processing techniques for sensor data mining able to reflect the dynamic nature of real-world context. However, few of these techniques provide a systematic view of the relationships between sensor data streams and correlated network behaviors. In this paper, an association model of inherent, data and network properties is presented and analyzed for a suite of event diffusion spotting applications. Based on the associated model, window-based in-network cooperation is conducted for sensitive event diffusion spotting. Experimental results verify the performance of our approach, and confirm the scalability of our association perspective of sensor properties in such event diffusion spotting networks.
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Cui, X., Li, Q., Zhao, B. (2008). An Association Model of Sensor Properties for Event Diffusion Spotting Sensor Networks. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds) Progress in WWW Research and Development. APWeb 2008. Lecture Notes in Computer Science, vol 4976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78849-2_20
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DOI: https://doi.org/10.1007/978-3-540-78849-2_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78848-5
Online ISBN: 978-3-540-78849-2
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