Networks with the Smallest Average Distance and the Largest Average Clustering
Molecular Networks
2010-07-28 v1 Disordered Systems and Neural Networks
Statistical Mechanics
Physics and Society
Quantitative Methods
Abstract
We describe the structure of the graphs with the smallest average distance and the largest average clustering given their order and size. There is usually a unique graph with the largest average clustering, which at the same time has the smallest possible average distance. In contrast, there are many graphs with the same minimum average distance, ignoring their average clustering. The form of these graphs is shown with analytical arguments. Finally, we measure the sensitivity to rewiring of this architecture with respect to the clustering coefficient, and we devise a method to make these networks more robust with respect to vertex removal.
Cite
@article{arxiv.1007.4031,
title = {Networks with the Smallest Average Distance and the Largest Average Clustering},
author = {Dionysios Barmpoutis and Richard M. Murray},
journal= {arXiv preprint arXiv:1007.4031},
year = {2010}
}