Scheduling parallelizable jobs online to maximize throughput

Abstract

In this paper, we consider scheduling parallelizable jobs online to maximize the throughput or profit of the schedule. In particular, a set of n jobs arrive online and each job Ji arriving at time ri has an associated function pi(t) which is the profit obtained for finishing job Ji at time t+ ri. Each job can have 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 and show O(1)-competitive algorithms using resource augmentation.