Optimal Data Incest Removal in Bayesian Decentralized Estimation Over a Sensor Network

TitleOptimal Data Incest Removal in Bayesian Decentralized Estimation Over a Sensor Network
Publication TypeConference Paper
Year of Publication2007
AuthorsBrehard, T., and V. Krishnamurthy
Conference NameAcoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
PaginationIII-173 -III-176
Date Publishedapr.
KeywordsBayes methods, Bayesian decentralized estimation, data incest management, integer optimization problem, network topology, optimal data incest removal, sensor network, telecommunication network management, telecommunication network topology, wireless sensor networks
Abstract

A fundamental issue in Bayesian decentralized estimation over a sensor network is the inadvertent multiple re-use of data also known as data incest. We show the relationship between data incest and the network topology by using a graph theoretical formulation. A novel necessary and sufficient condition based on the topology of the network is derived so that data incest management can be optimally achieved. This approach requires large storage capabilities at the sensor level. In the case of an arbitrary network, if the necessary and sufficient condition for data incest does not hold then finding a sub-optimal strategy requires solving a 0-1 integer optimization problem where the dimension of the vector to optimize increases with time. Numerical results illustrate the effectiveness of our approach

URLhttp://dx.doi.org/10.1109/ICASSP.2007.366500
DOI10.1109/ICASSP.2007.366500

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