Return a random topology using Barabasi-Albert preferential attachment model.
A topology of n nodes is grown by attaching new nodes each with m links that are preferentially attached to existing nodes with high degree.
More precisely, the Barabasi-Albert topology is built as follows. First, a line topology with m0 nodes is created. Then at each step, one node is added and connected to m existing nodes. These nodes are selected randomly with probability
Where i is the selected node and V is the set of nodes of the graph.
Parameters : | n : int
m : int
m0 : int
seed : int, optional
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Returns : | G : Topology |
Notes
The initialization is a graph with with m nodes connected by
edges.
It does not use the Barabasi-Albert method provided by NetworkX because it
does not allow to specify m0 parameter.
There are no disconnected subgraphs in the topology.
References
[R16] | A. L. Barabasi and R. Albert “Emergence of scaling in random networks”, Science 286, pp 509-512, 1999. |