Managing a Distributed Data Fusion Network

摘要

Networked data fusion applications require adaptive strategies to maximise their performance subject to fluctuating resource constraints. If the application is simply picture compilation (i.e., target tracking and identification) then Fisher/Shannon metrics provide a normative basis for approaching this problem. In this paper we demonstrate how information gain can be used to manage a constrained communication bandwidth in a decentralised tracking system that has to adapt to asymmetric communication bandwidth and data delays. When the sensor nodes are active participators in the information acquisition process, the relevance of information must also be considered. Specifically, what is the balance between the cost of information and the expected pay-off resulting from its application in a decision-making process? It is described how issues such as this fit into the formal framework of decentralised partially observed Markov decision process (DEC-POMDP) theory.