Mobilité d'un réseau de capteurs sans fil basée sur les méthodes à noyau. Ghadban, N., Honeine, P., Francis, C., Mourad-Chehade, F., Farah, J., & Kallas, M. In Actes du 24-ème Colloque GRETSI sur le Traitement du Signal et des Images, Brest, France, September, 2013.
Mobilité d'un réseau de capteurs sans fil basée sur les méthodes à noyau [pdf]Paper  abstract   bibtex   
Wireless sensor networks have received considerable attention during the last decade for efficient monitoring, due to their low cost, their easy deployment and their capacity to locally process information. This paper derives original mobility schemes that allow improving the tracking of a physical phenomenon. To this end, we use kernel-based methods to construct a local model for each sensor, using the learning process where the input is the position of the sensor and the output is the estimation of the physical phenomenon. We show that kernel-based methods provide an elegant way to optimize the model. This allows us to derive mobility schemes for sensors in such a way to improve the efficiency of the models, by minimizing the estimation error. Sensors are moved according to several optimization techniques, by considering the first and second derivatives of the approximation error. Experimentations aim at estimating a gas diffusion in the space at any location devoid of sensor.

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