Scale-free Models of Real-World Networks

Bela Bollobas

University of Memphis, TN and University of Cambridge, UK

April 25,
refreshments at 3:45pm


In 1998, Watts and Strogatz observed that many large-scale real-world networks, including neural networks, power grids, collaboration graphs, and the internet, have numerous common features that resemble properties of random graphs. It was also realized that the standard mean-field and lattice-based random graphs are not appropriate models of these large-scale networks, so we should look for other classes of random graphs. One of the main features demanded of these new random graphs is that they should be scale-free. The first such model was introduced by Barabasi and Albert in 1999; by now, numerous models of scale-free random graphs have been proposed and studied, mostly by computer simulations and heuristic analysis.

In the talk we shall review a number of these models, and present several recent rigorous results obtained jointly with Oliver Riordan, and some other results proved with Noam Berger, Christian Borgs, Jennifer Chayes and Oliver Riordan.

Speaker's Contact Info: bbolloba(at-sign)

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