期刊
SCIENTIFIC REPORTS
卷 3, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/srep02354
关键词
-
资金
- Network Science Collaborative Technology Alliance
- US Army Research Laboratory [W911NF-09-2-0053]
- Defense Advanced Research Projects Agency [11645021]
- Defense Threat Reduction Agency [WMD BRBAA07-J-2-0035]
Controlling complex systems is a fundamental challenge of network science. Recent advances indicate that control over the system can be achieved through a minimum driver node set (MDS). The existence of multiple MDS's suggests that nodes do not participate in control equally, prompting us to quantify their participations. Here we introduce control capacity quantifying the likelihood that a node is a driver node. To efficiently measure this quantity, we develop a random sampling algorithm. This algorithm not only provides a statistical estimate of the control capacity, but also bridges the gap between multiple microscopic control configurations and macroscopic properties of the network under control. We demonstrate that the possibility of being a driver node decreases with a node's in-degree and is independent of its out-degree. Given the inherent multiplicity of MDS's, our findings offer tools to explore control in various complex systems.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据