Generating Scale-free Networks with Adjustable Clustering Coefficient   Via Random Walks
  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. 
Carlos Herrera and Pedro J.Zufiria
physics.soc-ph cs.SI