IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v34y2017i4d10.1007_s10878-017-0135-z.html
   My bibliography  Save this article

A primal–dual online algorithm for the k-server problem on weighted HSTs

Author

Listed:
  • Wenbin Chen

    (Guangzhou University
    Nanjing University)

  • Fufang Li

    (Guangzhou University)

  • Jianxiong Wang

    (Guangzhou University)

  • Ke Qi

    (Guangzhou University)

  • Maobin Tang

    (Guangzhou University)

  • Xiuni Wang

    (Guangzhou University)

Abstract

In this paper, we show that there is a $$\frac{5}{2}\ell \cdot \ln (1+k)$$ 5 2 ℓ · ln ( 1 + k ) -competitive randomized algorithm for the k-sever problem on weighted Hierarchically Separated Trees (HSTs) with depth $$\ell $$ ℓ when $$n=k+1$$ n = k + 1 where n is the number of points in the metric space, which improved previous best competitive ratio $$12 \ell \ln (1+4\ell (1+k))$$ 12 ℓ ln ( 1 + 4 ℓ ( 1 + k ) ) by Bansal et al. (FOCS, pp 267–276, 2011).

Suggested Citation

  • Wenbin Chen & Fufang Li & Jianxiong Wang & Ke Qi & Maobin Tang & Xiuni Wang, 2017. "A primal–dual online algorithm for the k-server problem on weighted HSTs," Journal of Combinatorial Optimization, Springer, vol. 34(4), pages 1133-1146, November.
  • Handle: RePEc:spr:jcomop:v:34:y:2017:i:4:d:10.1007_s10878-017-0135-z
    DOI: 10.1007/s10878-017-0135-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-017-0135-z
    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/s10878-017-0135-z?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. Yinfeng Xu & Hongmei Li & Changzheng He & Li Luo, 2015. "The online $$k$$ k -server problem with max-distance objective," Journal of Combinatorial Optimization, Springer, vol. 29(4), pages 836-846, May.
    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.
    1. Shanxiu Jiang & Li Luo, 2019. "Online in-time service problem with minimal server assignment," Journal of Combinatorial Optimization, Springer, vol. 37(1), pages 114-122, January.

    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:34:y:2017:i:4:d:10.1007_s10878-017-0135-z. 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.