Real Network Control Understanding how complex networks are controlled has implications for a variety of real-world networks, from traffic safety to transcriptional control. Ruths and Ruths (p. 1373 ; see the Perspective by Onnela ) have developed a theoretical framework for analyzing individual controls within networks based on numbers of sources and sinks for information flow. By this method, the number of controls required by a network can be predicted and direct comparisons for the basis for control across networks of differing size, structure, and function can be made. Although three broad classes of real networks were observed, current, established random models of networks were insufficient to model their control structures.