[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/inm/ormoor/v48y2023i1p227-256.html
   My bibliography  Save this article

Load Balancing Under Strict Compatibility Constraints

Author

Listed:
  • Daan Rutten

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Debankur Mukherjee

    (H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract
Consider a system with N identical single-server queues and a number of task types, where each server is able to process only a small subset of possible task types. Arriving tasks select d ≥ 2 random compatible servers and join the shortest queue among them. The compatibility constraints are captured by a fixed bipartite graph between the servers and the task types. When the graph is complete bipartite, the mean-field approximation is accurate. However, such dense compatibility graphs are infeasible for large-scale implementation. We characterize a class of sparse compatibility graphs for which the mean-field approximation remains valid. For this, we introduce a novel notion, called proportional sparsity , and establish that systems with proportionally sparse compatibility graphs asymptotically match the performance of a fully flexible system. Furthermore, we show that proportionally sparse random compatibility graphs can be constructed, which reduce the server degree almost by a factor N / ln ( N ) compared with the complete bipartite compatibility graph.

Suggested Citation

  • Daan Rutten & Debankur Mukherjee, 2023. "Load Balancing Under Strict Compatibility Constraints," Mathematics of Operations Research, INFORMS, vol. 48(1), pages 227-256, February.
    • Handle: RePEc:inm:ormoor:v:48:y:2023:i:1:p:227-256
    DOI: 10.1287/moor.2022.1258
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/moor.2022.1258
    Download Restriction: no
    File URL: https://libkey.io/10.1287/moor.2022.1258?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
    ---><---

    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:inm:ormoor:v:48:y:2023:i:1:p:227-256. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.