  What is the underlying mechanism leading to power-law degree distributions of
many natural and artificial networks is still at issue. We consider that
scale-free networks emerges from self-organizing process, and such a evolving
model is introduced in this letter. At each time step, a new node is added to
the network and connect to some existing nodes randomly, instead of
"preferential attachment" introduced by Barab\'{a}si and Albert, and then the
new node will connect with its neighbors' neighbors at a fixed probability,
which is natural to collaboration networks and social networks of acquaintance
or other relations between individuals. The simulation results show that those
networks generated from our model are scale-free networks with satisfactorily
large clustering coefficient.
