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Networks with the Smallest Average Distance and the Largest Average Clustering
Abstract We describe the structure of the graphs wi …
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.
ore robust with respect to vertex removal.  +
Authors Dionysios Barmpoutis, Richard M Murray  +
ID 2010h  +
Source arXiv, q-bio.MN  +
Tag bm10-arxiv  +
Title Networks with the Smallest Average Distance and the Largest Average Clustering +
Type Preprint  +
Categories Papers
Modification date
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15 May 2016 06:16:17  +
URL
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http://www.cds.caltech.edu/~murray/preprints/bm10-arxiv.pdf  +
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Networks with the Smallest Average Distance and the Largest Average Clustering + Title
 

 

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