Flow of Control in Networks
Flow of Control in Networks
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DOI：
10.1126/science.1251746
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发表时间：
2014-03
期刊：
影响因子：
56.9
通讯作者：
J. Onnela
中科院分区：
文献类型：
--
作者：
J. Onnela
一个简单的框架可以根据控制流对复杂网络进行分类。[Also许多复杂的系统可以被看作是网络，其中节点代表系统元素，边对应于这些元素之间的交互。在这样的网络中，节点的子集-驱动节点-可以在由外部信号驱动时产生对整个网络的控制（1-3）。然而，要控制一个系统，不仅要知道哪些部分需要控制，还要知道为什么这些特定的部分需要控制。在本期的第1373页，Ruths和Ruths（4）提出了一个优雅的框架，阐明了网络中控制的起源。该框架根据节点如何影响网络中的控制流将节点分为三类。这种方法产生了控制配置文件，作者使用这些配置文件对大量的经验和合成网络进行分类。结果表明，来自不同领域但属于同一类别的网络可能比以前认为的更相似。
A simple framework allows the classification of complex networks based on the flow of control. [Also see Report by Ruths and Ruths] Many complex systems can be viewed as networks, in which nodes represent system elements and edges correspond to interactions between those elements. In such networks, a subset of nodes—the driver nodes—can yield control of the entire network when they are driven by external signals (1–3). However, to control a system, one must know not only what parts need to be controlled but also why these particular parts need to be controlled. On page 1373 of this issue, Ruths and Ruths (4) put forward an elegant framework that elucidates the origin of control in networks. The framework divides nodes into three categories based on how they affect the flow of control in networks. This approach gives rise to control profiles that the authors use to classify a host of empirical and synthetic networks. The results suggest that networks from different domains but in the same category may be more similar to one another than previously thought.