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Scheduling Parallelizable Jobs Online to Maximize Throughput

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LATIN 2018: Theoretical Informatics (LATIN 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10807))

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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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Author information

Authors and Affiliations

  1. Washington University in St. Louis, St. Louis, MO, 63130, USA

    Kunal Agrawal & Kefu Lu

  2. New Jersey Institute of Technology, Newark, NJ, 07102, USA

    Jing Li

  3. Carnegie Mellon University, Forbes Avenue, Pittsburgh, PA, 15213, USA

    Benjamin Moseley

Authors
  1. Kunal Agrawal
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  2. Jing Li
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  3. Kefu Lu
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  4. Benjamin Moseley
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Corresponding author

Correspondence to Kefu Lu .

Editor information

Editors and Affiliations

  1. Stony Brook University, Stony Brook, New York, USA

    Michael A. Bender

  2. Rutgers University, New Brunswick, New Jersey, USA

    Martín Farach-Colton

  3. Pace University, New York, New York, USA

    Miguel A. Mosteiro

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Agrawal, K., Li, J., Lu, K., Moseley, B. (2018). Scheduling Parallelizable Jobs Online to Maximize Throughput. In: Bender, M., Farach-Colton, M., Mosteiro, M. (eds) LATIN 2018: Theoretical Informatics. LATIN 2018. Lecture Notes in Computer Science(), vol 10807. Springer, Cham. https://doi.org/10.1007/978-3-319-77404-6_55

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  • DOI: https://doi.org/10.1007/978-3-319-77404-6_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77403-9

  • Online ISBN: 978-3-319-77404-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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