Scheduling Parallelizable Jobs Online to Maximize Throughput

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10807)

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 \(J_i\) arriving at time \(r_i\) has an associated function \(p_i(t)\) which is the profit obtained for finishing job \(J_i\) at time \(t+r_i\). 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.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Kunal Agrawal
    • 1
  • Jing Li
    • 2
  • Kefu Lu
    • 1
  • Benjamin Moseley
    • 3
  1. 1.Washington University in St. LouisSt. LouisUSA
  2. 2.New Jersey Institute of TechnologyNewarkUSA
  3. 3.Carnegie Mellon UniversityPittsburghUSA

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