  As a basic dynamic feature on complex networks, the property of random walk
has received a lot of attention in recent years. In this paper, we first
studied the analytical expression of the mean global first passage time (MGFPT)
on the 3-dimensional 3-level Sierpinski gasket network. Based on the
self-similar structure of the network, the correlation between the MGFPT and
the average trapping time (ATT) is found, and then the analytical expression of
the ATT is obtained. Finally, by establishing a joint network model, we further
give the standard process of solving the analytical expression of the ATT when
there is a set of trap nodes in the network. By illustrating examples and
numerical simulations, it can be proved that when the trap node sets are
different, the ATT will be quite different, but the the super-linear
relationship with the number of iterations will not be changed.
