Distributed least square for consensus building in sensor networks

Authors:
Fernando Pérez-Cruz;Sanjev Kulkarni
Affiliations:
Department of Electrical Engineering, Princeton University, Princeton, New Jersey and Department of Signal Theory and Communications, University Carlos III, Leganés, Madrid;Department of Electrical Engineering, Princeton University, Princeton, New Jersey
Venue:
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
Year:
2009

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Abstract

We present a novel mechanism for consensus building in sensor networks. The proposed algorithm has three main properties that make it suitable for general sensor-network learning. First, the proposed algorithm is based on robust nonparametric statistics and thereby needs little prior knowledge about the network and the function that needs to be estimated. Second, the algorithm uses only local information about the network and it communicates only with nearby sensors. Third, the algorithm is completely asynchronous and robust. It does not need to coordinate the sensors to estimate the underlying function and it is not affected if other sensors in the network stop working. Therefore, the proposed algorithm is an ideal candidate for sensor networks deployed in remote and inaccessible areas, which might need to change their objective once they have been set up.