Non asymptotic bounds in asynchronous sum-weight gossip protocols
Machine Learning
2021-11-22 v1 Machine Learning
Optimization and Control
Abstract
This paper focuses on non-asymptotic diffusion time in asynchronous gossip protocols. Asynchronous gossip protocols are designed to perform distributed computation in a network of nodes by randomly exchanging messages on the associated graph. To achieve consensus among nodes, a minimal number of messages has to be exchanged. We provides a probabilistic bound to such number for the general case. We provide a explicit formula for fully connected graphs depending only on the number of nodes and an approximation for any graph depending on the spectrum of the graph.
Cite
@article{arxiv.2111.10248,
title = {Non asymptotic bounds in asynchronous sum-weight gossip protocols},
author = {David Picard and Jérôme Fellus and Stéphane Garnier},
journal= {arXiv preprint arXiv:2111.10248},
year = {2021}
}
Comments
Unpublished work done circa 2016