Scheduling with Testing on Multiple Identical Parallel Machines

TL;DR

This paper studies online scheduling with testing on multiple identical machines, proposing algorithms with competitive ratios close to optimal for minimizing makespan under explorable uncertainty.

Contribution

It introduces new deterministic algorithms and bounds for scheduling with testing on multiple machines, improving understanding of competitive ratios in this setting.

Findings

Non-preemptive SBS algorithm with ratio ~3.1016 for large machine counts

Preemptive setting with a 2-competitive algorithm and tight lower bound

Improved algorithms for uniform testing times with better competitive ratios

Abstract

Scheduling with testing is a recent online problem within the framework of explorable uncertainty motivated by environments where some preliminary action can influence the duration of a task. Jobs have an unknown processing time that can be explored by running a test. Alternatively, jobs can be executed for the duration of a given upper limit. We consider this problem within the setting of multiple identical parallel machines and present competitive deterministic algorithms and lower bounds for the objective of minimizing the makespan of the schedule. In the non-preemptive setting, we present the SBS algorithm whose competitive ratio approaches $3.1016$ if the number of machines becomes large. We compare this result with a simple greedy strategy and a lower bound which approaches $2$. In the case of uniform testing times, we can improve the SBS algorithm to be $3$-competitive. For the preemptive case we provide a $2$-competitive algorithm and a tight lower bound which approaches the same value.