Control Centrality and Hierarchical Structure in Complex Networks

We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a...

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Main Authors: Liu, Yang-Yu, Slotine, Jean-Jacques, Barabasi, Albert-Laszlo
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Article
Language:en_US
Published: Public Library of Science 2013
Online Access:http://hdl.handle.net/1721.1/76263
https://orcid.org/0000-0002-7161-7812
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author Liu, Yang-Yu
Slotine, Jean-Jacques
Barabasi, Albert-Laszlo
author2 Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
author_facet Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Liu, Yang-Yu
Slotine, Jean-Jacques
Barabasi, Albert-Laszlo
author_sort Liu, Yang-Yu
collection MIT
description We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks.
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spelling mit-1721.1/762632022-10-03T07:39:01Z Control Centrality and Hierarchical Structure in Complex Networks Liu, Yang-Yu Slotine, Jean-Jacques Barabasi, Albert-Laszlo Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Massachusetts Institute of Technology. Department of Mechanical Engineering Massachusetts Institute of Technology. Nonlinear Systems Laboratory Slotine, Jean-Jacques We introduce the concept of control centrality to quantify the ability of a single node to control a directed weighted network. We calculate the distribution of control centrality for several real networks and find that it is mainly determined by the network’s degree distribution. We show that in a directed network without loops the control centrality of a node is uniquely determined by its layer index or topological position in the underlying hierarchical structure of the network. Inspired by the deep relation between control centrality and hierarchical structure in a general directed network, we design an efficient attack strategy against the controllability of malicious networks. 2013-01-15T21:41:14Z 2013-01-15T21:41:14Z 2012-09 2012-04 Article http://purl.org/eprint/type/JournalArticle 1932-6203 http://hdl.handle.net/1721.1/76263 Liu, Yang-Yu, Jean-Jacques Slotine, and Albert-László Barabási. “Control Centrality and Hierarchical Structure in Complex Networks.” Ed. Yamir Moreno. PLoS ONE 7.9 (2012): e44459. https://orcid.org/0000-0002-7161-7812 en_US http://dx.doi.org/10.1371/journal.pone.0044459 PLoS ONE Creative Commons Attribution http://creativecommons.org/licenses/by/2.5/ application/pdf Public Library of Science PLoS
spellingShingle Liu, Yang-Yu
Slotine, Jean-Jacques
Barabasi, Albert-Laszlo
Control Centrality and Hierarchical Structure in Complex Networks
title Control Centrality and Hierarchical Structure in Complex Networks
title_full Control Centrality and Hierarchical Structure in Complex Networks
title_fullStr Control Centrality and Hierarchical Structure in Complex Networks
title_full_unstemmed Control Centrality and Hierarchical Structure in Complex Networks
title_short Control Centrality and Hierarchical Structure in Complex Networks
title_sort control centrality and hierarchical structure in complex networks
url http://hdl.handle.net/1721.1/76263
https://orcid.org/0000-0002-7161-7812
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