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Adaptive Dynamics of Realistic Small-World Networks

Sourcetitle: 
European Conference on Complex Systems 2009
Year of publication: 
2009
PublicationType: 
Conference paper - peer reviewed

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.

Sourcepages: 
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