In this paper, we address information exchange problem in heterogeneous fusion networks (decision networks). A fusion network is a set of connected nodes in which fusion nodes (decision-agents: DAs) consume information produced by other sources nodes (e.g., sensors, other fusion nodes), and information is exchanged across a web of connected nodes. Information value is assessed based on partial utility function. This value, representing the DA's utility, is modeled as a time depending function. Routing in a fusion network is not just about getting data from one point to another. Routing needs to optimize a set of end-to-end goals driven by the application requirements, while considering network resources. We model this problem as a bi-objective optimization problem that maximizes the overall utility of the network and reliability of the generated paths. A multi-objective genetic algorithm (MOGA) is proposed to solve such an NP-hard problem. The empirical results are also presented. © 2013 Springer-Verlag.
CITATION STYLE
Masri, H., Guitouni, A., & Krichen, S. (2013). Towards efficient information exchange in fusion networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7895 LNAI, pp. 535–546). https://doi.org/10.1007/978-3-642-38610-7_49
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