IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v11y2015i7p120812.html
   My bibliography  Save this article

Approximation Algorithms for Maximum Link Scheduling under SINR-Based Interference Model

Author

Listed:
  • Zi-Ao Zhou
  • Chang-Geng Li

Abstract

A fundamental problem in wireless networks is the maximum link scheduling (MLS) problem. In this problem, interference is a key issue and past researchers have shown that determining reception using Signal-to-Interference plus Noise Ratio (SINR) is more realistic than graph-based interference models. Unfortunately, the MLS problem has been proven to be NP-hard for SINR interference models. To date, several approximation algorithms have been proposed to solve MLS under the SINR-based interference model. However, most of these works do not have either an approximation bound or a distributed version. To this end, we present a novel scheduling method with a constant approximation ratio which is much simpler and only 1/28 of it in past research. The improvement of constant Ï• also offers a better MLS set. In addition, based on our centralized method, we present a polynomial time, randomized, distributed algorithm, which only requires estimates of the number of links, and maximum and minimum link lengths. We prove its correctness and show that it can compute a MLS with time complexity of O ( lo g 2 n ) , where n is an estimate of the number of links.

Suggested Citation

  • Zi-Ao Zhou & Chang-Geng Li, 2015. "Approximation Algorithms for Maximum Link Scheduling under SINR-Based Interference Model," International Journal of Distributed Sensor Networks, , vol. 11(7), pages 120812-1208, July.
  • Handle: RePEc:sae:intdis:v:11:y:2015:i:7:p:120812
    DOI: 10.1155/2015/120812
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1155/2015/120812
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2015/120812?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
    ---><---

    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:sae:intdis:v:11:y:2015:i:7:p:120812. 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.