IEICE TRANSACTIONS on Information
How Centrality of Driver Nodes Affects Controllability of Complex Networks
Summary :
Recently, the controllability of complex networks has become a hot topic in the field of network science, where the driver nodes play a key and central role. Therefore, studying their structural characteristics is of great significance to understand the underlying mechanism of network controllability. In this paper, we systematically investigate the nodal centrality of driver nodes in controlling complex networks, we find that the driver nodes tend to be low in-degree but high out-degree nodes, and most of driver nodes tend to have low betweenness centrality but relatively high closeness centrality. We also find that the tendencies of driver nodes towards eigenvector centrality and Katz centrality show very similar behaviors, both high eigenvector centrality and high Katz centrality are avoided by driver nodes. Finally, we find that the driver nodes towards PageRank centrality demonstrate a polarized distribution, i.e., the vast majority of driver nodes tend to be low PageRank nodes whereas only few driver nodes tend to be high PageRank nodes.
- Publication
- IEICE TRANSACTIONS on Information Vol.E104-D No.8 pp.1340-1348
- Publication Date
- 2021/08/01
- Publicized
- 2021/05/20
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2020EDP7238
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence, Data Mining
Authors
Guang-Hua SONG
Zhejiang University
Xin-Feng LI
Zhejiang University
Zhe-Ming LU
Zhejiang University
Keyword
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Guang-Hua SONG, Xin-Feng LI, Zhe-Ming LU, "How Centrality of Driver Nodes Affects Controllability of Complex Networks" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 8, pp. 1340-1348, August 2021, doi: 10.1587/transinf.2020EDP7238.
Abstract: Recently, the controllability of complex networks has become a hot topic in the field of network science, where the driver nodes play a key and central role. Therefore, studying their structural characteristics is of great significance to understand the underlying mechanism of network controllability. In this paper, we systematically investigate the nodal centrality of driver nodes in controlling complex networks, we find that the driver nodes tend to be low in-degree but high out-degree nodes, and most of driver nodes tend to have low betweenness centrality but relatively high closeness centrality. We also find that the tendencies of driver nodes towards eigenvector centrality and Katz centrality show very similar behaviors, both high eigenvector centrality and high Katz centrality are avoided by driver nodes. Finally, we find that the driver nodes towards PageRank centrality demonstrate a polarized distribution, i.e., the vast majority of driver nodes tend to be low PageRank nodes whereas only few driver nodes tend to be high PageRank nodes.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2020EDP7238/_p
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@ARTICLE{e104-d_8_1340,
author={Guang-Hua SONG, Xin-Feng LI, Zhe-Ming LU, },
journal={IEICE TRANSACTIONS on Information},
title={How Centrality of Driver Nodes Affects Controllability of Complex Networks},
year={2021},
volume={E104-D},
number={8},
pages={1340-1348},
abstract={Recently, the controllability of complex networks has become a hot topic in the field of network science, where the driver nodes play a key and central role. Therefore, studying their structural characteristics is of great significance to understand the underlying mechanism of network controllability. In this paper, we systematically investigate the nodal centrality of driver nodes in controlling complex networks, we find that the driver nodes tend to be low in-degree but high out-degree nodes, and most of driver nodes tend to have low betweenness centrality but relatively high closeness centrality. We also find that the tendencies of driver nodes towards eigenvector centrality and Katz centrality show very similar behaviors, both high eigenvector centrality and high Katz centrality are avoided by driver nodes. Finally, we find that the driver nodes towards PageRank centrality demonstrate a polarized distribution, i.e., the vast majority of driver nodes tend to be low PageRank nodes whereas only few driver nodes tend to be high PageRank nodes.},
keywords={},
doi={10.1587/transinf.2020EDP7238},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - How Centrality of Driver Nodes Affects Controllability of Complex Networks
T2 - IEICE TRANSACTIONS on Information
SP - 1340
EP - 1348
AU - Guang-Hua SONG
AU - Xin-Feng LI
AU - Zhe-Ming LU
PY - 2021
DO - 10.1587/transinf.2020EDP7238
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2021
AB - Recently, the controllability of complex networks has become a hot topic in the field of network science, where the driver nodes play a key and central role. Therefore, studying their structural characteristics is of great significance to understand the underlying mechanism of network controllability. In this paper, we systematically investigate the nodal centrality of driver nodes in controlling complex networks, we find that the driver nodes tend to be low in-degree but high out-degree nodes, and most of driver nodes tend to have low betweenness centrality but relatively high closeness centrality. We also find that the tendencies of driver nodes towards eigenvector centrality and Katz centrality show very similar behaviors, both high eigenvector centrality and high Katz centrality are avoided by driver nodes. Finally, we find that the driver nodes towards PageRank centrality demonstrate a polarized distribution, i.e., the vast majority of driver nodes tend to be low PageRank nodes whereas only few driver nodes tend to be high PageRank nodes.
ER -
English
