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Group percolation in interdependent networks

Zexun Wang1,2, Dong Zhou3, and Yanqing Hu1,*

  • 1School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China
  • 2Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China
  • 3Simula Research Laboratory, 1325 Lysaker, Norway

  • *yanqing.hu.sc@gmail.com
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Phys. Rev. E 97, 032306 – Published 16 March, 2018

DOI: https://doi.org/10.1103/PhysRevE.97.032306

Abstract

In many real network systems, nodes usually cooperate with each other and form groups to enhance their robustness to risks. This motivates us to study an alternative type of percolation, group percolation, in interdependent networks under attack. In this model, nodes belonging to the same group survive or fail together. We develop a theoretical framework for this group percolation and find that the formation of groups can improve the resilience of interdependent networks significantly. However, the percolation transition is always of first order, regardless of the distribution of group sizes. As an application, we map the interdependent networks with intersimilarity structures, which have attracted much attention recently, onto the group percolation and confirm the nonexistence of continuous phase transitions.

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Phys. Rev. E 97, 032306– Published 16 March, 2018
  • Received 7 July 2017
  • Revised 30 December 2017
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