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Current command and control (C2) network models typically do not account for differences in attributes of nodes that belong to the same class; in addition, there is no provision in these models for the adequate description of operational relationships that exist between multiple combat entities with different attributes in real-world scenarios. To address these issues, we propose a method to model multilevel command and control supernetworks (MC2S) based on the attribute synergy prioritization and hypergraph theory. First, the characteristics of C2 supernetworks are analyzed to abstract their nodes and hyperedges, based on which, we propose the MC2S model, which consists of three layers and five networks. Second, the Term Frequency–Inverse Document Frequency and spatial distance algorithms are used to construct an attribute synergy prioritization-based strategy for the generation of intra-layer MC2S hyperedges, while the local-world (LW) selection is used to create an LW model-based method for the generation of inter-layer MC2S hyperedges. Through simulation experiments, we show that our model exhibits (approximately) scale-free properties as well as small-world properties, excellent cooperative engagement capabilities, and has a high level of network invulnerability. These findings will serve as a useful reference for the description of complex nodal (edge) relationships in C2 networks, network performance analyses, and deployment of complex combat mission networks.

Multilevel Command and Control Supernetwork Modeling Based on Attribute Synergy Prioritization