Cargando…

Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows

Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caus...

Descripción completa

Detalles Bibliográficos
Autores principales: Moussawi, A., Derzsy, N., Lin, X., Szymanski, B. K., Korniss, G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601003/
https://www.ncbi.nlm.nih.gov/pubmed/28916772
http://dx.doi.org/10.1038/s41598-017-11765-1
_version_ 1783264312007065600
author Moussawi, A.
Derzsy, N.
Lin, X.
Szymanski, B. K.
Korniss, G.
author_facet Moussawi, A.
Derzsy, N.
Lin, X.
Szymanski, B. K.
Korniss, G.
author_sort Moussawi, A.
collection PubMed
description Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caused by such failures. We introduce a stochastic method for optimal heterogeneous distribution of resources (node capacities) subject to a fixed total cost. Additionally, we design and compare the performance of networks with N-stable and (N-1)-stable network-capacity allocations by triggering cascades using various real-world node-attack and node-failure scenarios. We show that failure mitigation through increased node protection can be effectively achieved against single-node failures. However, mitigating against multiple node failures is much more difficult due to the combinatorial increase in possible sets of initially failing nodes. We analyze the robustness of the system with increasing protection, and find that a critical tolerance exists at which the system undergoes a phase transition, and above which the network almost completely survives an attack. Moreover, we show that cascade-size distributions measured in this region exhibit a power-law decay. Finally, we find a strong correlation between cascade sizes induced by individual nodes and sets of nodes. We also show that network topology alone is a weak predictor in determining the progression of cascading failures.
format Online
Article
Text
id pubmed-5601003
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-56010032017-09-20 Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows Moussawi, A. Derzsy, N. Lin, X. Szymanski, B. K. Korniss, G. Sci Rep Article Cascading failures are a critical vulnerability of complex information or infrastructure networks. Here we investigate the properties of load-based cascading failures in real and synthetic spatially-embedded network structures, and propose mitigation strategies to reduce the severity of damages caused by such failures. We introduce a stochastic method for optimal heterogeneous distribution of resources (node capacities) subject to a fixed total cost. Additionally, we design and compare the performance of networks with N-stable and (N-1)-stable network-capacity allocations by triggering cascades using various real-world node-attack and node-failure scenarios. We show that failure mitigation through increased node protection can be effectively achieved against single-node failures. However, mitigating against multiple node failures is much more difficult due to the combinatorial increase in possible sets of initially failing nodes. We analyze the robustness of the system with increasing protection, and find that a critical tolerance exists at which the system undergoes a phase transition, and above which the network almost completely survives an attack. Moreover, we show that cascade-size distributions measured in this region exhibit a power-law decay. Finally, we find a strong correlation between cascade sizes induced by individual nodes and sets of nodes. We also show that network topology alone is a weak predictor in determining the progression of cascading failures. Nature Publishing Group UK 2017-09-15 /pmc/articles/PMC5601003/ /pubmed/28916772 http://dx.doi.org/10.1038/s41598-017-11765-1 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Moussawi, A.
Derzsy, N.
Lin, X.
Szymanski, B. K.
Korniss, G.
Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
title Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
title_full Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
title_fullStr Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
title_full_unstemmed Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
title_short Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
title_sort limits of predictability of cascading overload failures in spatially-embedded networks with distributed flows
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5601003/
https://www.ncbi.nlm.nih.gov/pubmed/28916772
http://dx.doi.org/10.1038/s41598-017-11765-1
work_keys_str_mv AT moussawia limitsofpredictabilityofcascadingoverloadfailuresinspatiallyembeddednetworkswithdistributedflows
AT derzsyn limitsofpredictabilityofcascadingoverloadfailuresinspatiallyembeddednetworkswithdistributedflows
AT linx limitsofpredictabilityofcascadingoverloadfailuresinspatiallyembeddednetworkswithdistributedflows
AT szymanskibk limitsofpredictabilityofcascadingoverloadfailuresinspatiallyembeddednetworkswithdistributedflows
AT kornissg limitsofpredictabilityofcascadingoverloadfailuresinspatiallyembeddednetworkswithdistributedflows