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Disintegrating spatial networks based on region centrality.

Zhi-Gang Wang1, Ye Deng1, Ze Wang1

  • 1International Academic Center of Complex Systems, Beijing Normal University, Zhuhai 519087, People's Republic of China.

Chaos (Woodbury, N.Y.)
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Summary
This summary is machine-generated.

This study introduces a novel strategy for network disintegration, focusing on spatial networks to maximize fragmentation efficiently. The method prioritizes nodes near the network

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Area of Science:

  • Network science
  • Graph theory
  • Spatial analysis

Background:

  • Disintegrating harmful networks is crucial for applications like counter-terrorism and epidemic control.
  • Existing methods for network fragmentation may lack efficiency or optimal cost-effectiveness.

Purpose of the Study:

  • To develop an optimal, cost-efficient strategy for disintegrating spatial networks.
  • To identify node or link removal sets that maximize network fragmentation.

Main Methods:

  • Introduction of a 'region centrality' metric, combining node degree and link count within a region.
  • Evaluation of the strategy on synthetic and real-world spatial networks.

Main Results:

  • The proposed strategy significantly outperforms conventional methods in effectiveness and efficiency.
  • The optimal disintegration strategy focuses on nodes with average degree, not just high-centrality nodes.

Conclusions:

  • The developed region centrality-based strategy offers a superior approach to network disintegration.
  • This method provides a more effective and efficient means for controlling harmful network spread.