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Information-defined networks: A communication network approach for network studies

The research of complex networks facilitates the progress of various disciplines, including biology, chemistry, social science, computer, and communication engineering. Recently, it is popular to utilize complex networks to study the communication networks, such as designing efficient routing strategies and robust communication networks. However, exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy. Because of this situation, this paper proposes an information-defined network (IDN) framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents. Specifically, each component and dynamic process in this framework can be defined by information. We show that the IDN framework promotes the research of unsolved problems in the current complex network field, especially for detecting new interaction types in real-world networks.