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Adaptive Dynamics of Realistic Small-World Networks

Olof Mogren ; Oskar Sandberg (Institutionen för matematiska vetenskaper) ; Vilhelm Verendel (Institutionen för energi och miljö, Fysisk resursteori) ; Devdatt Dubhashi (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers))
European Conference on Complex Systems 2009 p. 12. (2009)
[Konferensbidrag, refereegranskat]

Continuing in the steps of Jon Kleinberg’s and others celebrated work on decentralized search, we conduct an experimental analysis of destination sam- pling, a dynamic algorithm that produces small-world networks. We find that the algorithm adapts robustly to a wide variety of situations in realistic geographic net- works with synthetic test data and with real world data, even when vertices are unevenly and non-homogeneously distributed. We investigate the same algorithm in the case where some vertices are more popular destinations for searches than others, for example obeying power-laws. We find that the algorithm adapts and adjusts the networks ac- cording to the distributions, leading to improved per- formance. The ability of the dynamic process to adapt and create small worlds in such diverse settings suggests a possible mechanism by which such networks appear in nature.

Nyckelord: social networks, dynamics, algorithms, adaptive search

Denna post skapades 2010-07-13. Senast ändrad 2015-06-23.
CPL Pubid: 123846


Institutioner (Chalmers)

Institutionen för matematiska vetenskaperInstitutionen för matematiska vetenskaper (GU)
Institutionen för energi och miljö, Fysisk resursteori (2005-2017)
Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)



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