IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v12y2016i10p1550147716673930.html
   My bibliography  Save this article

Online auction-based resource scheduling in grid computing networks

Author

Listed:
  • Lili Ding
  • Long Chang
  • Lei Wang

Abstract

The aim of this article is to introduce a novel auction-based algorithm for grid computing wireless networks and resolve some incompetence with dynamic mechanisms. We develop a reverse online auction method to allocate grid resources, where the grid resource providers arrive dynamically and user broker has to make a multi-attribute decision whether to sell tasks or not before the end of current round. In our approach, a trade-some-with-forecast algorithm is proposed to help the user broker to utilize his forecast ability to allocate the grid resource in an online setting. Furthermore, two reverse online auction-based protocols are presented to demonstrate the resource scheduling in grid computing wireless networks. Experiments show that the reverse online auction-based with forecast protocol has better performance in comparison with the reverse online auction-based protocol. It is efficient in terms of auction stages, user satisfaction, and successful forecast.

Suggested Citation

  • Lili Ding & Long Chang & Lei Wang, 2016. "Online auction-based resource scheduling in grid computing networks," International Journal of Distributed Sensor Networks, , vol. 12(10), pages 15501477166, October.
    • Handle: RePEc:sae:intdis:v:12:y:2016:i:10:p:1550147716673930
    DOI: 10.1177/1550147716673930
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147716673930
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147716673930?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:sae:intdis:v:12:y:2016:i:10:p:1550147716673930. 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: SAGE Publications (email available below). General contact details of provider: .

    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.