Information properties of co-processing model on communication networks are investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. Considering the influence of a node to the global dynamical behavior, co-processing centrality is introduced for each node, which determines the relative importance of nodes and exhibits the capability that a node communicates information with its neighbor environment over the network in the diffusion process. Furthermore, a new parameter, co-processing entropy, is proposed to measure the interplay between co-processing centrality and diffusion dynamics. At last, the information function of the co-processing model is investigated to deeply detect the properties of the diffusion process. The experimental results on large-scale complex networks with Poisson distribution confirm our analytical prediction.
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