  This paper presents an algorithm for generating scale-free networks with
adjustable clustering coefficient. The algorithm is based on a random walk
procedure combined with a triangle generation scheme which takes into account
genetic factors; this way, preferential attachment and clustering control are
implemented using only local information. Simulations are presented which
support the validity of the scheme, characterizing its tuning capabilities.
