Title :
A new distributed algorithm for parametric data modeling in wireless sensor networks
Author :
Maréchal, Nicolas ; Pierrot, Jean-Benoît ; Gorce, Jean-Marie
Author_Institution :
CEA-LETI MINATEC, Grenoble, France
Abstract :
Sensor networks aim at monitoring events and phenomena occurring in their environment and providing useful information to one or several end users.When a global knowledge of sensed data is needed, techniques from data gathering, statistical estimation and parametric modeling can be used. While the two first methods require respectively a large amount of energy and a knowledge of statistical dependencies between measurements, a new simple algorithm for fitting a parametric model to sensed data is proposed in this article. The novelty and advantages of this approach stands in its intrinsic robustness to packet losses and asynchronous data exchanges. Moreover, this algorithm is intituively efficient as it uses the broadcasting nature of the wireless medium.
Keywords :
sensor fusion; statistical analysis; wireless sensor networks; data fusion; data gathering; distributed algorithm; parametric data modeling; parametric modeling; statistical estimation; wireless sensor networks; Broadcasting; Costs; Distributed algorithms; Energy storage; Hardware; Parametric statistics; Robustness; Sensor phenomena and characterization; Vectors; Wireless sensor networks; Distributed algorithm; consensus algorithms; data fusion.; networked systems; sensor networks;
Conference_Titel :
Signal Processing Advances in Wireless Communications, 2009. SPAWC '09. IEEE 10th Workshop on
Conference_Location :
Perugia
Print_ISBN :
978-1-4244-3695-8
Electronic_ISBN :
978-1-4244-3696-5
DOI :
10.1109/SPAWC.2009.5161746