Optimal Online Contention Resolution Schemes via Ex-Ante Prophet Inequalities

TL;DR

This paper develops optimal online contention resolution schemes for matroids by leveraging ex-ante prophet inequalities, achieving the first optimal 1/2-approximate OCRS and introducing optimal (1-1/e)-random order CRSs.

Contribution

It introduces the first optimal 1/2-approximate OCRS for matroids and designs optimal (1-1/e)-random order CRSs, connecting prophet inequalities with online contention resolution.

Findings

First optimal 1/2-approximate OCRS for matroids.

Optimal (1-1/e)-random order CRSs for matroids.

Reduction of OCRS design to ex-ante prophet inequalities.

Abstract

Online contention resolution schemes (OCRSs) were proposed by Feldman, Svensson, and Zenklusen as a generic technique to round a fractional solution in the matroid polytope in an online fashion. It has found applications in several stochastic combinatorial problems where there is a commitment constraint: on seeing the value of a stochastic element, the algorithm has to immediately and irrevocably decide whether to select it while always maintaining an independent set in the matroid. Although OCRSs immediately lead to prophet inequalities, these prophet inequalities are not optimal. Can we instead use prophet inequalities to design optimal OCRSs? We design the first optimal $1/2$-OCRS for matroids by reducing the problem to designing a matroid prophet inequality where we compare to the stronger benchmark of an ex-ante relaxation. We also introduce and design optimal $(1-1/e)$-random order CRSs for matroids, which are similar to OCRSs but the arrival is chosen uniformly at random.