DocumentCode :
1811495
Title :
A reconfiguration framework for self-organizing distributed state estimators
Author :
van Leeuwen, Coen ; Sijs, Joris ; Papp, Z.
Author_Institution :
TNO Tech. Sci., The Hague, Netherlands
fYear :
2013
fDate :
9-12 July 2013
Firstpage :
499
Lastpage :
506
Abstract :
A sensor network operating under changing operational conditions will have to adapt to its environment, topology and system performance. In order to obtain this flexible behavior, a reconfiguration framework is proposed for distributed signal processing solutions. The considered example in this article is distributed Kalman filtering, whereas the reconfiguration framework is based on a first order logic reasoner to find a feasible configuration in a dynamic execution context. In a simulated scenario of a greenhouse temperature field estimation, the proposed system can minimize the state estimation error, while satisfying the systems constraints such as battery life, communication bandwidth or reliability and timeliness of response.
Keywords :
Kalman filters; computerised instrumentation; formal logic; greenhouses; inference mechanisms; signal processing; state estimation; battery life; communication bandwidth; distributed Kalman filtering; distributed signal processing solutions; dynamic execution context; first order logic reasoner; greenhouse temperature field estimation; reconfiguration framework; self-organizing distributed state estimators; sensor network; state estimation error; Hardware; Kalman filters; Merging; Nickel; State estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3
Type :
conf
Filename :
6641321
Link To Document :
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