ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2408.05495
18
1

Asynchronous Approximate Agreement with Quadratic Communication

10 August 2024
Mose Mizrahi Erbes
Roger Wattenhofer
ArXivPDFHTML
Abstract

We consider an asynchronous network of nnn message-sending parties, up to ttt of which are byzantine. We study approximate agreement, where the parties obtain approximately equal outputs in the convex hull of their inputs. The seminal protocol of Abraham, Amit and Dolev [OPODIS '04] achieves approximate agreement in R\mathbb{R}R with the optimal resilience t<n3t < \frac{n}{3}t<3n​ by making each party reliably broadcast its input. This takes Ω(n2)\Omega(n^2)Ω(n2) messages per reliable broadcast, or Ω(n3)\Omega(n^3)Ω(n3) messages in total. In this work, we present optimally resilient asynchronous approximate agreement protocols which forgo reliable broadcast and thus require communication proportional to n2n^2n2 instead of n3n^3n3. First, we achieve ω\omegaω-dimensional barycentric agreement with O(ωn2)\mathcal{O}(\omega n^2)O(ωn2) small messages. Then, we achieve edge agreement in a tree of diameter DDD with ⌈log⁡2D⌉\lceil \log_2 D \rceil⌈log2​D⌉ iterations of a multivalued graded consensus variant for which we design an efficient protocol. This results in a O(log⁡1ε)\mathcal{O}(\log\frac{1}{\varepsilon})O(logε1​)-round protocol for ε\varepsilonε-agreement in [0,1][0, 1][0,1] with O(n2log⁡1ε)\mathcal{O}(n^2\log\frac{1}{\varepsilon})O(n2logε1​) messages and O(n2log⁡1εlog⁡log⁡1ε)\mathcal{O}(n^2\log\frac{1}{\varepsilon}\log\log\frac{1}{\varepsilon})O(n2logε1​loglogε1​) bits of communication, improving over the state of the art which matches this complexity only when the inputs are all either 000 or 111. Finally, we extend our edge agreement protocol to achieve edge agreement in Z\mathbb{Z}Z and thus ε\varepsilonε-agreement in R\mathbb{R}R with quadratic communication, in O(log⁡Mε)\mathcal{O}(\log\frac{M}{\varepsilon})O(logεM​) rounds where MMM is the maximum honest input magnitude.

View on arXiv
Comments on this paper