To seek key nodes and improve network robustness

the dynamic convergence complex network model and its node importance evaluation method are proposed for wired and wireless integrating layered networks. Considering characteristic of dynamic convergence complex networks

parameters including edge connection probability

path connection probability

network connection probability

convergence node proportion

convergence node distribution and convergence path proportion are designed. Based on node importance evaluation indexes in single-layer complex networks

the node degree centrality

node betweenness centrality and node convergence centrality in dynamic convergence complex networks are presented. Node convergence centrality of convergence nodes indicates their contribution to network convergence

and that of non-convergence nodes indicates their auxiliary effect to network convergence

especially they are used as relay nodes among convergence nodes. At last

node importance evaluation is implemented considering network topology structure and its dynamic convergence characteristic. Typical example results of improved dynamic convergence kite networks show that the proposed method can comprehensively depict the node importance in dynamic convergence complex networks. Simulation network composed of fiber communication network and satellite communication network is designed by NS2

further indicating the effectiveness of the proposed method.