The advancement of network science over the past 20 years has created the expectation that we will soon be able to systematically control the behavior of complex network systems and in turn address numerous outstanding scientific problems, from cell reprogramming and drug target identification to cascade control and self-healing infrastructure development . This expectation is not without reason, given that control technologies have been part of human development for over 2,000 years .
While significant progress has been made, our current ability to control is still limited in many systems. This is not so much from lack of available technologies to actuate specific network elements as from challenges imposed by unique characteristics of large real networks to designing system-level control actions . These limiting characteristics include the combination of high dimensionality, nonlinearity, and constraints on the interventions, which set networks apart from other systems to which control has been traditionally applied . Recent progress on developing control techniques scalable to large networks has been driven by the design of new approaches.
Sensitive Dependence on Network Structure: Analog of Chaos and Opportunity for Control
By Adilson E. Motter and Takashi Nishikawa