Brief Announcement: Scheduling Parallelizable Jobs Online to Maximize Throughput

Abstract

We consider scheduling parallelizable jobs online to maximize the throughput or profit of the schedule. A set of n jobs arrive online and each job Ji has an associated function pi(t), the profit obtained for finishing job Ji at time t. Each job has its own arbitrary non-increasing profit function. We consider the case where each job is a parallel job that can be represented as a directed acyclic graph (DAG). We give the first non-trivial results for the profit scheduling problem for DAG jobs showing O(1)-competitive algorithms using resource augmentation.