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
Link To Document