Accession Number:

ADA588967

Title:

A Randomized Gossip Consenus Algorithm on Convex Metric Spaces

Descriptive Note:

Technical rept.

Corporate Author:

MARYLAND UNIV COLLEGE PARK INST FOR SYSTEMS RESEARCH

Report Date:

2012-01-01

Pagination or Media Count:

21.0

Abstract:

A consensus problem consists of a group of dynamic agents who seek to agree upon certain quantities of interest. This problem can be generalized in the context of convex metric spaces that extend the standard notion of convexity. In this paper we introduce and analyze a randomized gossip algorithm for solving the generalized consensus problem on convex metric spaces. We study the convergence properties of the algorithm using stochastic differential equations theory. We show that the dynamics of the distances between the states of the agents can be upper bounded by the dynamics of a stochastic differential equation driven by Poisson counters. In addition, we introduce instances of the generalized consensus algorithm for several examples of convex metric spaces together with numerical simulations.

Subject Categories:

  • Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE