Effective augmentation of complex networks

Wang, J, Yu, X and Stone, L 2016, 'Effective augmentation of complex networks', Scientific Reports, vol. 6, 25627, pp. 1-6.

Document type: Journal Article
Collection: Journal Articles

Attached Files
Name Description MIMEType Size
n2006074593.pdf Published Version application/pdf 927.68KB
Title Effective augmentation of complex networks
Author(s) Wang, J
Yu, X
Stone, L
Year 2016
Journal name Scientific Reports
Volume number 6
Article Number 25627
Start page 1
End page 6
Total pages 6
Publisher Nature
Abstract Networks science plays an enormous role in many aspects of modern society from distributing electrical power across nations to spreading information and social networking amongst global populations. While modern networks constantly change in size, few studies have sought methods for the difficult task of optimising this growth. Here we study theoretical requirements for augmenting networks by adding source or sink nodes, without requiring additional driver-nodes to accommodate the change i.e., conserving structural controllability. Our "effective augmentation" algorithm takes advantage of clusters intrinsic to the network topology, and permits rapidly and efficient augmentation of a large number of nodes in one time-step. "Effective augmentation" is shown to work successfully on a wide range of model and real networks. The method has numerous applications (e.g. study of biological, social, power and technological networks) and potentially of significant practical and economic value.
Subject Litigation, Adjudication and Dispute Resolution
Keyword(s) Controllability
DOI - identifier 10.1038/srep25627
Copyright notice This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
ISSN 2045-2322
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
Altmetric details:
Access Statistics: 84 Abstract Views, 26 File Downloads  -  Detailed Statistics
Created: Thu, 29 Jun 2017, 08:27:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us