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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/15750

Title: Onion-like networks are both robust and resilient
Authors: Hayashi, Yukio
Uchiyama, Naoya
Keywords: optimal robust onion-like networks
feedback vertex set
adaptive capacity in resilience
cascading failures
Issue Date: 2018-07-26
Publisher: Springer Nature
Magazine name: Scientific Reports
Volume: 8
Start page: Article number: 11241
DOI: 10.1038/s41598-018-29626-w
Abstract: Tolerant connectivity and flow transmission within capacity are crucial functions as network. However, the threats to malicious attacks based on intelligent node selections and rapid breakdown by cascading overload failures increase more and more with large blackout or congestion in our contemporary networking systems and societies. It has been recently suggested that interwoven loops protect the network functions from such damages, but it is a computationally intractable combinatorial problem to maximize a set of necessary nodes for loops in order to improve the robustness. We propose a new method by enhancing loops in the incremental growth for constructing onion-like networks with positive degree-degree correlations, whose topological structure has the optimal tolerance of connectivity against attacks in the state-of-the-art. Moreover, we find out that onion-like networks acquire adaptive capacity in resilience by a change of routing policy for flow control to absorb cascading overload failures triggered by a single attack and simultaneous multi-attacks. The inhibitory effect is stronger than that in scale-free networks found in many real systems.
Rights: © The Author(s) 2018. Yukio Hayashi, and Naoya Uchiyama, Scientific Reports, 8, 2018, Article number: 11241. DOI:10.1038/s41598-018-29626-w. 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/.
URI: http://hdl.handle.net/10119/15750
Material Type: publisher
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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