In information fusion applications, it is mainly used in a centralized way, by gathering the data on a single node before computation. In this paper, a ...
In this paper, we present an experimental study of its properties. This algorithm is self-stabilizing and runs on unreliable message passing networks. It ...
In this paper, a distributed algorithm is proposed to compute the neighborhood confidence of each node, by combining all the data of its neighbors using an ...
First we explain how the pro- cessing of uncertain and imprecise data in a distributed system can be modeled by algebraic operators over a specific finite set, ...
Then, it is shown that when adding a discounting to the cautious operator, it becomes an r-operator and the distributed algorithm becomes self-stabilizing. This ...
Measure : • Pressure measurement : interval I ⊂ R+. • Pressure gradient : interval ∆I ⊂ R. • Simple mass function : • Only two subsets : ∆I and R.
A distributed algorithm is proposed to compute the neighborhood confidence of each node, by combining all the data of its neighbors using an adaptation of ...
Abstract. The Theory of Belief Functions is a formal framework for reasoning with uncertainty that is well suited for representing unreliable.
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In this paper, we deal with the problem of distributed data fusion in unsafe large-scale sensor networks. Data fusion application is the phase of processing ...
Self-Stabilizing Distributed Data Fusion by Bertrand Ducourthial, Véronique Cherfaoui, Thierry Denoeux published in Lecture Notes in Computer Science.