Return a random topology using the extended Barabasi-Albert preferential attachment model.
Differently from the original Barabasi-Albert model, this model takes into account the presence of local events, such as the addition of new links or the rewiring of existing links.
More precisely, the Barabasi-Albert topology is built as follows. First, a topology with m0 isolated nodes is created. Then, at each step: with probability p add m new links between existing nodes, selected with probability:
with probability q rewire m links. Each link to be rewired is selected as
follows: a node i is randomly selected and a link is randomly removed from
it. The node i is then connected to a new node randomly selected with
probability ,
with probability
add a new node and attach it to m nodes of
the existing topology selected with probability
Repeat the previous step until the topology comprises n nodes in total.
Parameters : | n : int
m : int
m0 : int
p : float
q : float
seed : int, optional
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Returns : | G : Topology |
References
[R20] | A. L. Barabasi and R. Albert “Topology of evolving networks: local events and universality”, Physical Review Letters 85(24), 2000. |