Distributed Spanner Approximation
Keren Censor-Hillel, Michal Dory

TL;DR
This paper investigates the complexity and algorithms for constructing approximate minimum spanners in distributed networks, establishing lower bounds, model separations, and providing new approximation algorithms.
Contribution
It presents the first separation between LOCAL and CONGEST models for a local approximation problem and introduces a polynomial local computation algorithm for minimum 2-spanners.
Findings
Lower bounds for directed k-spanner approximation in CONGEST model.
First separation between LOCAL and CONGEST models for approximation problems.
A polynomial local computation algorithm for minimum 2-spanners with optimal ratio.
Abstract
We address the fundamental network design problem of constructing approximate minimum spanners. Our contributions are for the distributed setting, providing both algorithmic and hardness results. Our main hardness result shows that an -approximation for the minimum directed -spanner problem for requires rounds using deterministic algorithms or rounds using randomized ones, in the CONGEST model of distributed computing. Combined with the constant-round -approximation algorithm in the LOCAL model of [Barenboim, Elkin and Gavoille, 2016], as well as a polylog-round -approximation algorithm in the LOCAL model that we show here, our lower bounds for the CONGEST model imply a strict separation between the LOCAL and CONGEST models. Notably, to the best of our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
