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Received:October 16, 2010Revised:October 16, 2010
基金项目:This work was partly supported by the National Natural Science Foundation of China-Key Program (No. 61032001) and the National Natural Science Foundation of China (No. 60828006).
Sensor selection for parameterized random field estimation in wireless sensor networks
Yang WENG,Wendong XIAO,Lihua XIE
(School of Electrical and Electronic Engineering, Nanyang Technological University; School of Mathematics, Sichuan University;Institute for Infocomm Research)
We consider the random field estimation problem with parametric trend in wireless sensor networks where the field can be described by unknown parameters to be estimated. Due to the limited resources, the network selects only a subset of the sensors to perform the estimation task with a desired performance under the D-optimal criterion.We propose a greedy sampling scheme to select the sensor nodes according to the information gain of the sensors. A distributed algorithm is also developed by consensus-based incremental sensor node selection through information quality computation for and message exchange among neighboring sensors. Simulation results show the good performance of the proposed algorithms.
Key words:  Random field estimation  Parametric trend  Wireless sensor network  Sensor selection  NP-completeness  Distributed processing