Byzantine Fault-Tolerance in Decentralized Optimization under Minimal Redundancy
Abstract
This paper considers the problem of Byzantine fault-tolerance in multi-agent decentralized optimization. In this problem, each agent has a local cost function. The goal of a decentralized optimization algorithm is to allow the agents to cooperatively compute a common minimum point of their aggregate cost function. We consider the case when a certain number of agents may be Byzantine faulty. Such faulty agents may not follow a prescribed algorithm, and they may share arbitrary or incorrect information with other non-faulty agents. Presence of such Byzantine agents renders a typical decentralized optimization algorithm ineffective. We propose a decentralized optimization algorithm with provable exact fault-tolerance against a bounded number of Byzantine agents, provided the non-faulty agents have a minimal redundancy.
Keywords
Cite
@article{arxiv.2009.14763,
title = {Byzantine Fault-Tolerance in Decentralized Optimization under Minimal Redundancy},
author = {Nirupam Gupta and Thinh T. Doan and Nitin H. Vaidya},
journal= {arXiv preprint arXiv:2009.14763},
year = {2020}
}
Comments
An extension of our prior work on fault-tolerant distributed optimization, for the server-based system architecture (https://dl.acm.org/doi/10.1145/3382734.3405748), to the more general peer-to-peer system architecture