IDEAS home Printed from https://ideas.repec.org/a/wly/intnem/v33y2023i2ne2223.html
   My bibliography  Save this article

Optimal network‐aware virtual data center embedding

Author

Listed:
  • Ameni Hbaieb
  • Mahdi Khemakhem

Abstract

Recently, the virtual data center embedding (VDCE) problem has drawn significant attention because of a growing need for efficient means of data center resource allocation. By ensuring a set of virtual data center (VDC) integration requests coming from his customers, among the main concern of an infrastructure provider is the maximization of the utilization rate of data center resources and benefits. However, existing VDCE solutions mostly focus on consolidating virtual machines in a single physical data center. Therefore, in this work, we improve the consolidated targets techniques, that consider only the virtual machines integration, by the consideration of network devices and fabrics (e.g., switches and paths/links). We consider new unreleased constraints such as multiple virtual nodes of the same request co‐location, and intermediate node requirements when a virtual link is mapped. To address the above problem, in this paper, we propose a binary linear programming‐based model, called BLP‐VDCE, to solve the VDCE problem with network‐aware consideration. This model ensures a simultaneous consolidated embedding of virtual nodes and virtual links. Extensive simulations show that solving the proposed BLP‐VDCE model can efficiently embed VDC requests with a high physical resource utilization rate.

Suggested Citation

  • Ameni Hbaieb & Mahdi Khemakhem, 2023. "Optimal network‐aware virtual data center embedding," International Journal of Network Management, John Wiley & Sons, vol. 33(2), March.
  • Handle: RePEc:wly:intnem:v:33:y:2023:i:2:n:e2223
    DOI: 10.1002/nem.2223
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nem.2223
    Download Restriction: no

    File URL: https://libkey.io/10.1002/nem.2223?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
    ---><---

    References listed on IDEAS

    as
    1. Ameni Hbaieb & Mahdi Khemakhem & Maher Ben Jemaa, 2021. "Virtual Machine Placement with Disk Anti-colocation Constraints Using Variable Neighborhood Search Heuristic," Information Systems Frontiers, Springer, vol. 23(5), pages 1245-1271, September.
    Full references (including those not matched with items on IDEAS)

    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.

      More about this item

      Statistics

      Access and download statistics

      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:wly:intnem:v:33:y:2023:i:2:n:e2223. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1099-1190 .

      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.