Modelling cascading failures in networks with the harmonic closeness
Many studies on cascading failures adopt the degree or the betweenness of a node to define its load. From a novel perspective, we propose an approach to obtain initial loads considering the harmonic closeness and the impact of neighboring nodes. Based on simulation results for different adjustable p...
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description | Many studies on cascading failures adopt the degree or the betweenness of a node to define its load. From a novel perspective, we propose an approach to obtain initial loads considering the harmonic closeness and the impact of neighboring nodes. Based on simulation results for different adjustable parameter θ, local parameter δ and proportion of attacked nodes f, it is found that in scale-free networks (SF networks), small-world networks (SW networks) and Erdos-Renyi networks (ER networks), there exists a negative correlation between optimal θ and δ. By the removal of the low load node, cascading failures are more likely to occur in some cases. In addition, we find a valuable result that our method yields better performance compared with other methods in SF networks with an arbitrary f, SW and ER networks with large f. Moreover, the method concerning the harmonic closeness makes these three model networks more robust for different average degrees. Finally, we perform the simulations on twenty real networks, whose results verify that our method is also effective to distribute the initial load in different real networks. |
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From a novel perspective, we propose an approach to obtain initial loads considering the harmonic closeness and the impact of neighboring nodes. Based on simulation results for different adjustable parameter θ, local parameter δ and proportion of attacked nodes f, it is found that in scale-free networks (SF networks), small-world networks (SW networks) and Erdos-Renyi networks (ER networks), there exists a negative correlation between optimal θ and δ. By the removal of the low load node, cascading failures are more likely to occur in some cases. In addition, we find a valuable result that our method yields better performance compared with other methods in SF networks with an arbitrary f, SW and ER networks with large f. Moreover, the method concerning the harmonic closeness makes these three model networks more robust for different average degrees. Finally, we perform the simulations on twenty real networks, whose results verify that our method is also effective to distribute the initial load in different real networks.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0243801</identifier><identifier>PMID: 33493179</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Biology and Life Sciences ; Communication networks ; Computer and Information Sciences ; Computer Communication Networks ; Computer Simulation ; Engineering and Technology ; Failure ; Failure analysis ; Failure mode and effects analysis ; Gene Regulatory Networks ; Harmonic analysis ; Information Services ; Laboratories ; Load ; Loads (forces) ; Mathematical models ; Methods ; Models, Theoretical ; Nodes ; Parameters ; Physical Sciences ; Propagation ; Protein Interaction Maps ; Research and Analysis Methods ; Robustness ; Simulation ; Social Networking ; Social Sciences ; Stress concentration ; Traffic control</subject><ispartof>PloS one, 2021-01, Vol.16 (1), p.e0243801-e0243801</ispartof><rights>COPYRIGHT 2021 Public Library of Science</rights><rights>2021 Hao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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From a novel perspective, we propose an approach to obtain initial loads considering the harmonic closeness and the impact of neighboring nodes. Based on simulation results for different adjustable parameter θ, local parameter δ and proportion of attacked nodes f, it is found that in scale-free networks (SF networks), small-world networks (SW networks) and Erdos-Renyi networks (ER networks), there exists a negative correlation between optimal θ and δ. By the removal of the low load node, cascading failures are more likely to occur in some cases. In addition, we find a valuable result that our method yields better performance compared with other methods in SF networks with an arbitrary f, SW and ER networks with large f. Moreover, the method concerning the harmonic closeness makes these three model networks more robust for different average degrees. Finally, we perform the simulations on twenty real networks, whose results verify that our method is also effective to distribute the initial load in different real networks.</description><subject>Algorithms</subject><subject>Biology and Life Sciences</subject><subject>Communication networks</subject><subject>Computer and Information Sciences</subject><subject>Computer Communication Networks</subject><subject>Computer Simulation</subject><subject>Engineering and Technology</subject><subject>Failure</subject><subject>Failure analysis</subject><subject>Failure mode and effects analysis</subject><subject>Gene Regulatory Networks</subject><subject>Harmonic analysis</subject><subject>Information Services</subject><subject>Laboratories</subject><subject>Load</subject><subject>Loads (forces)</subject><subject>Mathematical models</subject><subject>Methods</subject><subject>Models, Theoretical</subject><subject>Nodes</subject><subject>Parameters</subject><subject>Physical 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One</addtitle><date>2021-01-25</date><risdate>2021</risdate><volume>16</volume><issue>1</issue><spage>e0243801</spage><epage>e0243801</epage><pages>e0243801-e0243801</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Many studies on cascading failures adopt the degree or the betweenness of a node to define its load. From a novel perspective, we propose an approach to obtain initial loads considering the harmonic closeness and the impact of neighboring nodes. Based on simulation results for different adjustable parameter θ, local parameter δ and proportion of attacked nodes f, it is found that in scale-free networks (SF networks), small-world networks (SW networks) and Erdos-Renyi networks (ER networks), there exists a negative correlation between optimal θ and δ. By the removal of the low load node, cascading failures are more likely to occur in some cases. In addition, we find a valuable result that our method yields better performance compared with other methods in SF networks with an arbitrary f, SW and ER networks with large f. Moreover, the method concerning the harmonic closeness makes these three model networks more robust for different average degrees. Finally, we perform the simulations on twenty real networks, whose results verify that our method is also effective to distribute the initial load in different real networks.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33493179</pmid><doi>10.1371/journal.pone.0243801</doi><tpages>e0243801</tpages><orcidid>https://orcid.org/0000-0003-0996-1345</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Biology and Life Sciences Communication networks Computer and Information Sciences Computer Communication Networks Computer Simulation Engineering and Technology Failure Failure analysis Failure mode and effects analysis Gene Regulatory Networks Harmonic analysis Information Services Laboratories Load Loads (forces) Mathematical models Methods Models, Theoretical Nodes Parameters Physical Sciences Propagation Protein Interaction Maps Research and Analysis Methods Robustness Simulation Social Networking Social Sciences Stress concentration Traffic control |
title | Modelling cascading failures in networks with the harmonic closeness |
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