Title
Structural Controllability Of Complex Networks Based On Preferential Matching
Abstract
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.
Year
DOI
Venue
2013
10.1371/journal.pone.0112039
PLOS ONE
Keywords
Field
DocType
computer simulation,algorithms
Small number,Complex system,Controllability,Computer science,Theoretical computer science,Complex network,Network analysis,Artificial neural network,Blossom algorithm,The Internet
Journal
Volume
Issue
ISSN
9
11
1932-6203
Citations 
PageRank 
References 
1
0.37
11
Authors
4
Name
Order
Citations
PageRank
Xi-zhe Zhang1388.94
Lv Tianyang2338.49
XueYing Yang310.37
Bin Zhang4627.17