Abstract
Navigation of mobile wireless sensor networks and fast target acquisition without a map are two challenging problems in search and rescue applications. In this paper, we propose and evaluate a novel Gradient Driven method, called GraDrive. Our approach integrates per-node prediction with global collaborative prediction to estimate the position of a stationary target and to direct mobile nodes towards the target along the shortest path. We demonstrate that a high accuracy in localization can be achieved much faster than other random work models without any assistance from stationary sensor networks. We evaluate our model through a light-intensity matching experiment in MicaZ motes, which indicates that our model works well in a wireless sensor network environment. Through simulation, we demonstrate almost a 40% reduction in the target acquisition time, compared to a random walk model, while obtaining less than 2 unit error in target position estimation.
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhang, Q., Sobelman, G., He, T. (2006). Gradient-Driven Target Acquisition in Mobile Wireless Sensor Networks. In: Cao, J., Stojmenovic, I., Jia, X., Das, S.K. (eds) Mobile Ad-hoc and Sensor Networks. MSN 2006. Lecture Notes in Computer Science, vol 4325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11943952_31
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DOI: https://doi.org/10.1007/11943952_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49932-9
Online ISBN: 978-3-540-49933-6
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