Sensor network localization for moving sensors

Update Item Information
Publication Type pre-print
School or College College of Engineering
Department Computing, School of
Creator Venkatasubramanian, Suresh
Other Author Agarwal, A.; Daumé III, H.; Phillips, J. M.
Title Sensor network localization for moving sensors
Date 2012-01-01
Description Sensor network localization (SNL) is the problem of determining the locations of the sensors given sparse and usually noisy inter-communication distances among them. In this work we propose an iterative algorithm named PLACEMENT to solve the SNL problem. This iterative algorithm requires an initial estimation of the locations and in each iteration, is guaranteed to reduce the cost function. The proposed algorithm is able to take advantage of the good initial estimation of sensor locations making it suitable for localizing moving sensors, and also suitable for the refinement of the results produced by other algorithms. Our algorithm is very scalable. We have experimented with a variety of sensor networks and have shown that the proposed algorithm outperforms existing algorithms both in terms of speed and accuracy in almost all experiments. Our algorithm can embed 120,000 sensors in less than 20 minutes.
Type Text
Publisher Classical Association of the Middle West and South
First Page 202
Last Page 209
Language eng
Bibliographic Citation Agarwal, A., Daumé III, H., Phillips, J. M., & Venkatasubramanian, S. (2012). Sensor network localization for moving sensors. Proceedings - 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012, no. 6406442, 202-9.
Rights Management (c)Classical Association of the Middle West and South
Format Medium application/pdf
Format Extent 287,117 bytes
Identifier uspace,18187
ARK ark:/87278/s68k7tw3
Setname ir_uspace
ID 708326
Reference URL https://collections.lib.utah.edu/ark:/87278/s68k7tw3
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