Structural controllability of complex networks based on preferential matching.
Minimum driver node sets (MDSs) play an important role in studying the structural controllability of complex networks. Recent research has shown that MDSs tend to avoid high-degree nodes. However, this observation is based on the analysis of a small number of MDSs, because enumerating all of the MDSs of a network is a #P problem. Therefore, past research has not been sufficient to arrive at a convincing conclusion. In this paper, first, we propose a preferential matching algorithm to find MDSs that have a specific degree property. Then, we show that the MDSs obtained by preferential matching can be composed of high- and medium-degree nodes. Moreover, the experimental results also show that the average degree of the MDSs of some networks tends to be greater than that of the overall network, even when the MDSs are obtained using previous research method. Further analysis shows that whether the driver nodes tend to be high-degree nodes or not is closely related to the edge direction of the network.
College of Information Science and Engineering, Northeastern University, Shenyang, China.
Xizhe
X
Zhang
College of Computer Science and Technology, Harbin Engineering University, Harbin, China; College of Computer Science and Technology, Tsinghua University, Beijing, China; Audit Research Institute, National Audit Office, Beijing, China.
Tianyang
T
Lv
College of Information Science and Engineering, Northeastern University, Shenyang, China.
XueYing
X
Yang
College of Information Science and Engineering, Northeastern University, Shenyang, China.
Bin
B
Zhang
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D008962:Models, Theoretical; D016571:Neural Networks, Computer