• DocumentCode
    511194
  • Title

    Evolution of Reference Networks with Fitness Inheritance

  • Author

    Jialin, Yang ; Bo, Cheng ; Junliang, Chen

  • Author_Institution
    State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    25-27 Dec. 2009
  • Firstpage
    213
  • Lastpage
    217
  • Abstract
    The vertex connectivity of many large networks follows a scale-free power-law distribution. BA model and many other BA-derived models reproduce such property and acquire a special status. The most distinct characteristic of these models is that during the preferential attachment process the choice of old vertices is based on the connectivity of the old vertices and there is no relationship between new vertices´ property and old ones´. In this article we present a new model that bases its choice of old vertices on the fitness of the old vertices and the fitness of new vertices is partially determined by the old ones. Based on the new model, both theoretical analysis and simulation show that the connectivity distribution of networks generated by our model follows an exponential distribution and loses the scale-free property. Also the differences between our model and existing models and the relationships between them are discussed.
  • Keywords
    complex networks; exponential distribution; BA-derived models; exponential distribution; fitness inheritance; reference networks; scale-free power-law distribution; vertex connectivity; Aging; Analytical models; Complex networks; Computer applications; Computer networks; Distributed computing; Joining processes; Power generation; Power system modeling; Telecommunication computing; fitness; fitness inheritance; power-law; reference network; scale-free network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-0-7695-3930-0
  • Electronic_ISBN
    978-1-4244-5423-5
  • Type

    conf

  • DOI
    10.1109/IFCSTA.2009.173
  • Filename
    5384600