Nearly Optimal Bounds for Distributed Wireless Scheduling in the SINR Model

TL;DR

This paper presents a distributed algorithm for wireless scheduling in the SINR model that achieves an $O( ext{log } n)$ approximation, matching centralized algorithms, and proves this bound is optimal.

Contribution

It introduces a distributed $O( ext{log } n)$-approximation algorithm for wireless scheduling in the SINR model that improves analysis and proves the optimality of this bound.

Findings

Distributed algorithm achieves $O( ext{log } n)$ approximation.

Matching lower bound shows no distributed algorithm can do better.

Applicable in arbitrary metric space with various power assignments.

Abstract

We study the wireless scheduling problem in the SINR model. More specifically, given a set of $n$ links, each a sender-receiver pair, we wish to partition (or \emph{schedule}) the links into the minimum number of slots, each satisfying interference constraints allowing simultaneous transmission. In the basic problem, all senders transmit with the same uniform power. We give a distributed $O(\log n)$-approximation algorithm for the scheduling problem, matching the best ratio known for centralized algorithms. It holds in arbitrary metric space and for every length-monotone and sublinear power assignment. It is based on an algorithm of Kesselheim and V\"ocking, whose analysis we improve by a logarithmic factor. We show that every distributed algorithm uses $\Omega(\log n)$ slots to schedule certain instances that require only two slots, which implies that the best possible absolute performance guarantee is logarithmic.