Improving Complex Network Controllability via Link Prediction

Document Type

Conference Proceeding

Source of Publication

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Publication Date

1-1-2019

Abstract

© 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Complex network is a network structure composed of a large number of nodes and complex relationships between these nodes. Using complex network can model many systems in real life. The individual in the system corresponds to the node in the network and the relationship between these individuals corresponds to the edge in the network. The controllability of complex networks is to study how to enable the network to arrive at the desired state from any initial state by external input signals. The external input signals transmit to the whole network through some nodes in the network, and these nodes are called driver node. For the study of controllability of complex network, it is mainly to judge whether the network is controllable or not and how to select the appropriate driver nodes at present. If a network has a high controllability, the network will be easy to control. However, complex networks are vulnerable and will cause declining of controllability. Therefore, we propose in this paper a link prediction-based method to make the network more robust to different modes of attacking. Through experiments we have validated the effectiveness of the proposed method.

ISBN

9783030323875

ISSN

1867-8211

Publisher

Springer

Volume

294 LNCIST

First Page

84

Last Page

97

Disciplines

Computer Sciences

Keywords

Complex networks, Link prediction, Network controllability

Scopus ID

85076180465

Indexed in Scopus

yes

Open Access

no

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