Blog: How to Control Complex Networks

How to Control Complex Networks
MIT News (05/12/11) Anne Trafton

Researchers at the Massachusetts Institute of Technology (MIT) and Northeastern University have developed a computational model that can analyze any type of complex network and find the critical points that can be used to control the entire system. The method can be used to reprogram adult cells and identify new drug targets, among other applications, says MIT professor Jean-Jacques Slotine. The researchers developed an algorithm that determines how many nodes in a network need to be controlled for total network control. They then adapted the algorithm to show how many points are needed and where those points are located. The number of points needed depends on the network's degree distribution, which describes the number of connections per node. The researchers applied their model to several real-life networks, including cell phone networks, social networks, and neuronal networks, calculating the percentage of points that need to be controlled in order to gain total control of the system. The researchers found that sparse networks require a higher number of controlled points than denser networks. "The area of control of networks is a very important one, and although much work has been done in this area, there are a number of open problems of outstanding practical significance," says Northeastern professor Adilson Motter.

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