IDEAS home Printed from https://ideas.repec.org/a/spr/eurphb/v45y2005i3p385-390.html
   My bibliography  Save this article

Properties of weighted structured scale-free networks

Author

Listed:
  • Zhi-Xi Wu
  • Xin-Jian Xu
  • Ying-Hai Wang

Abstract

A simple model for weighted structured scale-free (WSSF) networks is proposed. The growth dynamics of the network is based on a naive weight-driven deactivation mechanism which couples the establishment of new active vertices and the weights’ dynamical evolution. Simulations show that all the interesting statistical properties of the generated network (vertices degree, vertices strength and links weight) display good right-skewed distribution observed in many realistic systems. Particularly, if the constant bias factor in deactivation probability is appropriately chosen, a power law distribution P(k)∼k - γ for vertices total degree k with the exponent γ=3 is obtained. As a survey of the model, the epidemic spreading process in WSSF networks is studied based on the standard susceptible-infected (SI) model. The spreading velocity reaches a peak very quickly after the infection outbreaks which is similar to the case of infection propagation in other heterogeneous networks; and in the long time propagation it decays approximately with an exponential form. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2005

Suggested Citation

  • Zhi-Xi Wu & Xin-Jian Xu & Ying-Hai Wang, 2005. "Properties of weighted structured scale-free networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 45(3), pages 385-390, June.
  • Handle: RePEc:spr:eurphb:v:45:y:2005:i:3:p:385-390
    DOI: 10.1140/epjb/e2005-00188-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1140/epjb/e2005-00188-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1140/epjb/e2005-00188-1?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sabek, M. & Pigorsch, U., 2023. "Local assortativity in weighted and directed complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).

    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:spr:eurphb:v:45:y:2005:i:3:p:385-390. 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.