Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree

Network controllability and its robustness have been widely studied. However, analytical methods to calculate network controllability with respect to node in- and out-degree targeted removals are currently lacking. This paper develops methods, based on generating functions for the in- and out-degree...

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Main Authors: Fenghua Wang, Robert E. Kooij
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Entropy
Subjects:
Online Access:https://www.mdpi.com/1099-4300/25/4/656
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author Fenghua Wang
Robert E. Kooij
author_facet Fenghua Wang
Robert E. Kooij
author_sort Fenghua Wang
collection DOAJ
description Network controllability and its robustness have been widely studied. However, analytical methods to calculate network controllability with respect to node in- and out-degree targeted removals are currently lacking. This paper develops methods, based on generating functions for the in- and out-degree distributions, to approximate the minimum number of driver nodes needed to control directed networks, during node in- and out-degree targeted removals. By validating the proposed methods on synthetic and real-world networks, we show that our methods work reasonably well. Moreover, when the fraction of the removed nodes is below 10% the analytical results of random removals can also be used to predict the results of targeted node removals.
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spelling doaj.art-676b2f94085d42a3bf3979b351be78042023-11-17T19:09:12ZengMDPI AGEntropy1099-43002023-04-0125465610.3390/e25040656Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-DegreeFenghua Wang0Robert E. Kooij1Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, 2628 CD Delft, The NetherlandsFaculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, 2628 CD Delft, The NetherlandsNetwork controllability and its robustness have been widely studied. However, analytical methods to calculate network controllability with respect to node in- and out-degree targeted removals are currently lacking. This paper develops methods, based on generating functions for the in- and out-degree distributions, to approximate the minimum number of driver nodes needed to control directed networks, during node in- and out-degree targeted removals. By validating the proposed methods on synthetic and real-world networks, we show that our methods work reasonably well. Moreover, when the fraction of the removed nodes is below 10% the analytical results of random removals can also be used to predict the results of targeted node removals.https://www.mdpi.com/1099-4300/25/4/656controllabilitycomplex networksnode removals
spellingShingle Fenghua Wang
Robert E. Kooij
Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
Entropy
controllability
complex networks
node removals
title Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
title_full Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
title_fullStr Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
title_full_unstemmed Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
title_short Robustness of Network Controllability with Respect to Node Removals Based on In-Degree and Out-Degree
title_sort robustness of network controllability with respect to node removals based on in degree and out degree
topic controllability
complex networks
node removals
url https://www.mdpi.com/1099-4300/25/4/656
work_keys_str_mv AT fenghuawang robustnessofnetworkcontrollabilitywithrespecttonoderemovalsbasedonindegreeandoutdegree
AT robertekooij robustnessofnetworkcontrollabilitywithrespecttonoderemovalsbasedonindegreeandoutdegree