Multisensor Data Fusion
Sensor management using an active sensing approach
Signal Processing
Decentralised coordination of low-power embedded devices using the max-sum algorithm
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2
Agent Technologies for Sensor Networks
IEEE Intelligent Systems
Overlapping coalition formation for efficient data fusion in multi-sensor networks
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
A survey on power control issues in wireless sensor networks
IEEE Communications Surveys & Tutorials
IEEE Communications Magazine
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Decentralizing optimization problems across a network can reduce the time required to achieve a solution. We consider a wide-area surveillance sensor network observing an environment by varying the state of each sensor so as to assign it to one or more moving objects. The aim is to maximize an arbitrary utility function related to object tracking or object identification, using graph marginalization in the form of belief propagation. The algorithm performs well in an example application with six heterogeneous sensors. In larger network simulations, the time savings owing to decentralization quickly exceed 90%, with no reduction in optimality.