The Clustering Coefficient of a graph measures the extent to which vertices adjacent to any vertex v are
adjacent to each other as well.   Specifically, the clustering coefficient for a certain node v is defined
as the number of edges in v's neighborhood (i.e. the subgraph which consists of v's neighbors but not
v) divided by the total number of edges possible (i.e. the clique of size = v's neighbors).   The
Clustering Coefficient for the graph is the average of the clustering coefficient for all nodes in the
graph.  Typical AS topologies obtained from NLANR exhibit CC values between 0.3-0.4.

This metric along with the Clustering Coefficient metric measure the small-world properties of a
graph.  Intuitively, a small-world graph is a graph which has a larger clustering coefficient than a
random graph with the same path length.

Contributors:   D.J. Watts, S.H. Stogatz
Reference:      [WS98] Collective Dynamics of "small-world" networks, in Nature 393.
Implemented by: BRITE Development Team
