  Due to wide applications in diverse fields, random walks subject to
stochastic resetting have attracted considerable attention in the last decade.
In this paper, we study discrete-time random walks on complex network with
multiple resetting nodes. Using a renewal approach, we derive exact expressions
of the occupation probability of the walker in each node and mean-field
first-passage time between arbitrary two nodes. All the results are relevant to
the spectral properties of the transition matrix in the absence of resetting.
We demonstrate our results on circular networks, stochastic block models, and
Barab\'asi-Albert scale-free networks, and find the advantage of the resetting
processes to multiple resetting nodes in global searching on such networks.
