Spatial network disintegration based on spatial coverage

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NETL
NSTL
Elsevier

外文摘要：© 2024 Elsevier LtdThe problem of network disintegration, such as interrupting rumor spreading networks and dismantling terrorist networks, involves evaluating changes in network performance. However, traditional metrics primarily focus on the topological structure and often neglect the crucial spatial attributes of nodes and edges, thereby failing to capture the spatial functional losses. Here we first introduce the concept of spatial coverage to evaluate the spatial network performance, which is defined as the convex hull area of the largest connected component. Then a greedy algorithm is proposed to maximize the reduction of the convex hull area through strategic node removals. Extensive experiments verified that the spatial coverage metric can effectively quantify changes in the performance of spatial networks, and the proposed algorithm can maximize the reduction of the convex hull area of the largest connected component compared to genetic algorithm and centrality strategies. Specifically, our algorithm reduces the convex hull area by up to 30% compared to the best-performing strategy. These results indicate that the critical nodes influencing network performance are a combination of numerous peripheral spatial leaf nodes and a few central spatial core nodes. This study substantially enhances our understanding of spatial network robustness and provides a novel perspective for network optimization.

外文关键词：

Critical nodesGreedy algorithmNetwork disintegrationNetwork performanceSpatial coverageSpatial network

作者：

Deng Y.、Wang Z.、Xiao Y.、Shen X.、Wu J.、Kurths J.

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作者单位：

Department of Systems Science Faculty of Arts and Sciences Beijing Normal University||International Academic Center of Complex Systems Beijing Normal University

Department of Systems Science Faculty of Arts and Sciences Beijing Normal University||International Academic Center of Complex Systems Beijing Normal University||School of Systems Science Beijing Normal University

Department of Systems Science Faculty of Arts and Sciences Beijing Normal UniversityDepartment of Systems Science Faculty of Arts and Sciences Beijing Normal University||International Academic Center of Complex Systems Beijing Normal University||

Research Domain Complexity Science Potsdam Institute for Climate Impact Research||Department of Physics Humboldt-Universität zu Berlin

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出版年：

2025

DOI：

10.1016/j.ress.2024.110525

Reliability engineering & system safety

SCI

ISSN：0951-8320

年,卷(期)：2025.253(Jan.)

参考文献量79