IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v44y2022i5d10.1007_s10878-022-00892-9.html
   My bibliography  Save this article

Online data caching in edge-cloud collaborative system with the data center

Author

Listed:
  • Xinxin Han

    (Shenzhen Polytechnic)

  • Sijia Dai

    (Chinese Academy of Sciences)

  • Guichen Gao

    (Chinese Academy of Sciences)

  • Yang Wang

    (Chinese Academy of Sciences)

  • Yong Zhang

    (Chinese Academy of Sciences)

Abstract

In edge computing, the edge node can provide certain accessible storage and computing resources for the surrounding users. Caching data on the edge node can quickly retrieve the required data and complete the user’s requests with low delay. However, the resources of edge servers are limited and sometimes have to gain the data by transfering from other servers or buying from data centers at the cloud. Traditionally, data center is just regard as a place of purchasing data, and the data is always available for the buyer after purchase. However, we believe that these data have a validity period. After the buyer purchases the data, it only provides limited calls for free. Based on this assumption, in this paper, we study the data caching problem in the edge-cloud collaborative system to minimize the total cost. Without knowing the information of users’ future request flow, we propose an online algorithm. What’s more, the asymptotic competition ratio of the algorithm in the worst case is 3.

Suggested Citation

  • Xinxin Han & Sijia Dai & Guichen Gao & Yang Wang & Yong Zhang, 2022. "Online data caching in edge-cloud collaborative system with the data center," Journal of Combinatorial Optimization, Springer, vol. 44(5), pages 3351-3363, December.
    • Handle: RePEc:spr:jcomop:v:44:y:2022:i:5:d:10.1007_s10878-022-00892-9
    DOI: 10.1007/s10878-022-00892-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-022-00892-9
    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/s10878-022-00892-9?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.

    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:jcomop:v:44:y:2022:i:5:d:10.1007_s10878-022-00892-9. 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: 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.