Topology for Distributed Inference on Graphs

Author

Kar, Soummya ; Aldosari, Saeed ; Moura, José M F

Author_Institution

Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA

Volume

56

Issue

6

fYear

2008

fDate

6/1/2008 12:00:00 AM

Firstpage

2609

Lastpage

2613

Abstract

Let N decision-makers collaborate to reach a decision. We consider iterative distributed inference with local intersensor communication, which, under simplifying assumptions, is equivalent to distributed average consensus. We show that, under appropriate conditions, the topology given by the nonbipartite Ramanujan graphs optimizes the convergence rate of this distributed algorithm.

Keywords

convergence of numerical methods; decision making; distributed algorithms; distributed sensors; graph theory; iterative methods; telecommunication network topology; decision making; distributed average consensus; iterative distributed inference algorithm convergence; local intersensor communication; nonbipartite Ramanujan graph; sensor network topology design; Algorithm design and analysis; Collaboration; Communication channels; Convergence; Distributed algorithms; Graph theory; Inference algorithms; Iterative algorithms; Laplace equations; Network topology; Algebraic connectivity; Cayley; Laplacian; Ramanujan; consensus algorithm; distributed detection; random graphs; sensor networks; small-world; spectral graph theory; topology optimization;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/TSP.2008.923536

Filename

4524051