Evidence map›Paper›PMID 39202163›Full record

ArticleEntropy (Basel, Switzerland)2024

Percolation Transitions in Edge-Coupled Interdependent Networks with Reinforced Inter-Layer Links.

Junjie Zhang, Caixia Liu, Shuxin Liu, Kai Wang, Weifei Zang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Junjie ZhangInstitute of Information Technology, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China.ORCID 0000-0002-0014-1650
Caixia LiuInstitute of System Engineering, Academy of Military Sciences, Beijing 100091, China.ORCID 0009-0006-5977-6171
Shuxin LiuInstitute of Information Technology, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China.ORCID 0000-0002-3366-4466
Kai WangInstitute of Information Technology, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, China.ORCID 0009-0006-7318-6063
Weifei ZangDepartment of Information Systems Security, PLA Information Engineering University, Zhengzhou 450001, China.ORCID 0009-0002-9619-2395

Funding

Natural Science Foundation of Henan Province 242300420699Program of Song Shan Laboratory (Included in the management of Major Science and Technology Program of Henan Province) 221100210700-2
6 · The paper itself

Abstract

Prior research on cascading failures within interdependent networks has predominantly emphasized the coupling of nodes. Nevertheless, in practical networks, interactions often exist not just through the nodes themselves but also via the connections (edges) linking them, a configuration referred to as edge-coupled interdependent networks. Past research has shown that introducing a certain percentage of reinforced nodes or connecting edges can prevent catastrophic network collapses. However, the effect of reinforced inter-layer links in edge-coupled interdependent networks has yet to be addressed. Here, we develop a theoretical framework for studying percolation models in edge-coupled interdependent networks by introducing a proportion of reinforced inter-layer links and deriving detailed expressions for the giant and finite components and the percolation phase transition threshold. We find that there exists a required minimum proportion of the reinforced inter-layer links to prevent abrupt network collapse, which serves as a boundary to distinguish different phase transition types of a network. We provide both analytical and numerical solutions for random and scale-free networks, demonstrating that the proposed method exhibits superior reinforcement efficiency compared to intra-layer link reinforcement strategies. Theoretical analysis, simulation results, and real network systems validate our model and indicate that introducing a specific proportion of reinforced inter-layer links can prevent abrupt system failure and enhance network robustness in edge-coupled interdependent networks.

Indexed as

edge-coupled interdependent networksphase transitionsreinforcedrobustness

Identifiers

PMID39202163
PMCPMC11353759

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.