Resilient Distributed Averaging

TL;DR

This paper introduces a distributed averaging algorithm resilient to Byzantine adversaries, relying on graph robustness, with proven convergence and verified effectiveness through simulations.

Contribution

It presents a novel resilient averaging algorithm that guarantees convergence despite Byzantine adversaries, based on graph robustness analysis.

Findings

Algorithm converges under strong graph robustness.

Topology analysis links connectivity metrics to resilience.

Simulations confirm effectiveness under specified conditions.

Abstract

In this paper, a fully distributed averaging algorithm in the presence of adversarial Byzantine agents is proposed. The algorithm is based on a resilient retrieval procedure, where all non-Byzantine nodes send their own initial values and retrieve those of other agents. We establish that the convergence of the proposed algorithm relies on strong robustness of the graph for locally bounded adversaries. A topology analysis in terms of time complexity and relation between connectivity metrics is also presented. Simulation results are provided to verify the effectiveness of the proposed algorithms under prescribed graph conditions.