IDEAS home Printed from https://ideas.repec.org/a/spr/jsched/v22y2019i4d10.1007_s10951-018-0576-y.html
   My bibliography  Save this article

Malleable scheduling for flows of jobs and applications to MapReduce

Author

Listed:
  • Viswanath Nagarajan

    (University of Michigan)

  • Joel Wolf

    (IBM T.J. Watson Research Center)

  • Andrey Balmin

    (Platfora Inc.)

  • Kirsten Hildrum

    (IBM T.J. Watson Research Center)

Abstract

This paper provides a unified family of algorithms with performance guarantees for malleable scheduling problems on flows. A flow represents a set of jobs with precedence constraints. Each job has a speedup function that governs the rate at which work is done on the job as a function of the number of processors allocated to it. In our setting, each speedup function is linear up to some job-specific processor maximum. A key aspect of malleable scheduling is that the number of processors allocated to any job is allowed to vary with time. The overall objective is to minimize either the total cost (minisum) or the maximum cost (minimax) of the flows. Our approach handles a very general class of cost functions, and in particular provides the first constant-factor approximation algorithms for total and maximum weighted completion time. Our motivation for this work was scheduling in MapReduce, and we also provide experimental evaluations that show good practical performance.

Suggested Citation

  • Viswanath Nagarajan & Joel Wolf & Andrey Balmin & Kirsten Hildrum, 2019. "Malleable scheduling for flows of jobs and applications to MapReduce," Journal of Scheduling, Springer, vol. 22(4), pages 393-411, August.
  • Handle: RePEc:spr:jsched:v:22:y:2019:i:4:d:10.1007_s10951-018-0576-y
    DOI: 10.1007/s10951-018-0576-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10951-018-0576-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10951-018-0576-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. Drozdowski & W. Kubiak, 1999. "Scheduling parallel tasks withsequential heads and tails," Annals of Operations Research, Springer, vol. 90(0), pages 221-246, January.
    2. Elisabeth Günther & Felix G. König & Nicole Megow, 2014. "Scheduling and packing malleable and parallel tasks with precedence constraints of bounded width," Journal of Combinatorial Optimization, Springer, vol. 27(1), pages 164-181, January.
    3. Robert McNaughton, 1959. "Scheduling with Deadlines and Loss Functions," Management Science, INFORMS, vol. 6(1), pages 1-12, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaohu Wu & Patrick Loiseau, 2024. "Algorithms for Scheduling Deadline-Sensitive Malleable Tasks," SN Operations Research Forum, Springer, vol. 5(2), pages 1-38, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elisabeth Lübbecke & Marco E. Lübbecke & Rolf H. Möhring, 2019. "Ship Traffic Optimization for the Kiel Canal," Operations Research, INFORMS, vol. 67(3), pages 791-812, May.
    2. Andrzej Kozik, 2017. "Handling precedence constraints in scheduling problems by the sequence pair representation," Journal of Combinatorial Optimization, Springer, vol. 33(2), pages 445-472, February.
    3. Liu Guiqing & Li Kai & Cheng Bayi, 2015. "Preemptive Scheduling with Controllable Processing Times on Parallel Machines," Journal of Systems Science and Information, De Gruyter, vol. 3(1), pages 68-76, February.
    4. Hoogeveen, J. A. & Lenstra, J. K. & Veltman, B., 1996. "Preemptive scheduling in a two-stage multiprocessor flow shop is NP-hard," European Journal of Operational Research, Elsevier, vol. 89(1), pages 172-175, February.
    5. Yung-Chia Chang & Kuei-Hu Chang & Ching-Ping Zheng, 2022. "Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards," Mathematics, MDPI, vol. 10(13), pages 1-21, July.
    6. Scholl, Armin & Becker, Christian, 2006. "State-of-the-art exact and heuristic solution procedures for simple assembly line balancing," European Journal of Operational Research, Elsevier, vol. 168(3), pages 666-693, February.
    7. C N Potts & V A Strusevich, 2009. "Fifty years of scheduling: a survey of milestones," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 41-68, May.
    8. Leah Epstein, 2023. "Parallel solutions for preemptive makespan scheduling on two identical machines," Journal of Scheduling, Springer, vol. 26(1), pages 61-76, February.
    9. Djellab, Housni & Djellab, Khaled, 2002. "Preemptive Hybrid Flowshop Scheduling problem of interval orders," European Journal of Operational Research, Elsevier, vol. 137(1), pages 37-49, February.
    10. Han, Bin & Zhang, Wenjun & Lu, Xiwen & Lin, Yingzi, 2015. "On-line supply chain scheduling for single-machine and parallel-machine configurations with a single customer: Minimizing the makespan and delivery cost," European Journal of Operational Research, Elsevier, vol. 244(3), pages 704-714.
    11. Huo, Yumei & Zhao, Hairong, 2015. "Total completion time minimization on multiple machines subject to machine availability and makespan constraints," European Journal of Operational Research, Elsevier, vol. 243(2), pages 547-554.
    12. Chen, Lin & Ye, Deshi & Zhang, Guochuan, 2018. "Parallel machine scheduling with speed-up resources," European Journal of Operational Research, Elsevier, vol. 268(1), pages 101-112.
    13. Xu, Jun & Wang, Jun-Qiang & Liu, Zhixin, 2022. "Parallel batch scheduling: Impact of increasing machine capacity," Omega, Elsevier, vol. 108(C).
    14. Zeynep Adak & Mahmure Övül Arıoğlu Akan & Serol Bulkan, 0. "Multiprocessor open shop problem: literature review and future directions," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    15. Jacques Carlier & Claire Hanen, 2024. "Measuring the slack between lower bounds for scheduling on parallel machines," Annals of Operations Research, Springer, vol. 338(1), pages 347-377, July.
    16. Mehdi Rajabi Asadabadi, 2017. "A developed slope order index (SOI) for bottlenecks in projects and production lines," Computational Management Science, Springer, vol. 14(2), pages 281-291, April.
    17. Jiang, Xiaojuan & Lee, Kangbok & Pinedo, Michael L., 2021. "Ideal schedules in parallel machine settings," European Journal of Operational Research, Elsevier, vol. 290(2), pages 422-434.
    18. Yiwei Jiang & Zewei Weng & Jueliang Hu, 2014. "Algorithms with limited number of preemptions for scheduling on parallel machines," Journal of Combinatorial Optimization, Springer, vol. 27(4), pages 711-723, May.
    19. Qian, Fubin & Strusevich, Vitaly & Gribkovskaia, Irina & Halskau, Øyvind, 2015. "Minimization of passenger takeoff and landing risk in offshore helicopter transportation: Models, approaches and analysis," Omega, Elsevier, vol. 51(C), pages 93-106.
    20. Yumei Huo, 2019. "Parallel machine makespan minimization subject to machine availability and total completion time constraints," Journal of Scheduling, Springer, vol. 22(4), pages 433-447, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jsched:v:22:y:2019:i:4:d:10.1007_s10951-018-0576-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.