Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published January 2012 | public
Journal Article

Quantized Consensus by Means of Gossip Algorithm

Abstract

This paper deals with the distributed averaging problem over a connected network of agents, subject to a quantization constraint. It is assumed that at each time update, only a pair of agents can update their own states in terms of the quantized data being exchanged. The agents are also required to communicate with one another in a stochastic fashion. It is shown that a quantized consensus is reached for an arbitrary quantizer by means of the stochastic gossip algorithm proposed in a recent paper. The expected value of the time at which a quantized consensus is reached is lower and upper bounded in terms of the topology of the graph for a uniform quantizer. In particular, it is shown that these bounds are related to the principal submatrices of the weighted Laplacian matrix. A convex optimization is also proposed to determine a set of probabilities used to pick a pair of agents that leads to a fast convergence of the gossip algorithm.

Additional Information

© 2011 IEEE. Manuscript received March 10, 2009; revised October 29, 2009; accepted June 16, 2011. Date of publication June 23, 2011; date of current version December 29, 2011. This work was supported by ONR MURI N00014-08-1-0747 "Scalable, Data-driven, and Provably-correct Analysis of Networks," ARO MURI W911NF-08-1-0233 "Tools for the Analysis and Design of Complex Multi-Scale Networks," and the Army's W911NF-09-D-0001 Institute for Collaborative Biotechnology. Recommended by Associate Editor H. Ishii. The authors would like to gratefully acknowledge J. C. Doyle for fruitful discussions on this topic.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023