Proceedings of the 6th international conference on Information processing in sensor networks
Energy scaling laws for distributed inference in random fusion networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
Energy-efficient routing for signal detection in wireless sensor networks
IEEE Transactions on Signal Processing
Incremental distributed identification of Markov random field models in wireless sensor networks
IEEE Transactions on Signal Processing
Serial distributed detection performance analysis in wireless sensor networks under noisy channel
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Lifetime maximization in wireless sensor networks with an estimation mission
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
IEEE Transactions on Wireless Communications
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
International Journal of Ad Hoc and Ubiquitous Computing
Reliable and energy efficient cooperative detection in wireless sensor networks
Computer Communications
Distributed routing for signal detection in wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
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In this paper, the detection of a correlated Gaussian field using a large multi-hop sensor network is investigated. A cooperative routing strategy is proposed by introducing a new link metric that characterizes the detection error exponent. Derived from the Chernoff information and Schweppe's likelihood recursion, this link metric captures the contribution of a given link to the decay rate of error probability and has the form of the capacity of a Gaussian channel with the sender transmitting the innovation of its measurement. For one-dimensional Gauss-Markov fields, the link metric can be represented explicitly as a function of the link length. Cooperative routing is achieved using the Kalman data aggregation and shortest path routing. Numerical simulations show that cooperative routing can be significantly more energy efficient than noncooperative routing for the same detection performance