Immunization and Targeted Destruction of Networks using Explosive Percolation

Pau Clusella, Peter Grassberger, Francisco J. Pérez-Reche, and Antonio Politi
Phys. Rev. Lett. 117, 208301 – Published 8 November 2016
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Abstract

A new method (“explosive immunization”) is proposed for immunization and targeted destruction of networks. It combines the explosive percolation (EP) paradigm with the idea of maintaining a fragmented distribution of clusters. The ability of each node to block the spread of an infection (or to prevent the existence of a large cluster of connected nodes) is estimated by a score. The algorithm proceeds by first identifying low score nodes that should not be vaccinated or destroyed, analogously to the links selected in EP if they do not lead to large clusters. As in EP, this is done by selecting the worst node (weakest blocker) from a finite set of randomly chosen “candidates.” Tests on several real-world and model networks suggest that the method is more efficient and faster than any existing immunization strategy. Because of the latter property it can deal with very large networks.

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  • Received 31 March 2016

DOI:https://doi.org/10.1103/PhysRevLett.117.208301

© 2016 American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsNetworksInterdisciplinary PhysicsStatistical Physics & Thermodynamics

Authors & Affiliations

Pau Clusella1,2, Peter Grassberger3,1, Francisco J. Pérez-Reche1,*, and Antonio Politi1

  • 1Institute for Complex Systems and Mathematical Biology, SUPA, University of Aberdeen, Aberdeen AB24 3UE, United Kingdom
  • 2Dipartimento di Fisica, Università di Firenze, via G. Sansone 1, I-50019 Sesto Fiorentino, Italy
  • 3JSC, FZ Jülich, D-52425 Jülich, Germany

  • *Corresponding author. fperez-reche@abdn.ac.uk

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Issue

Vol. 117, Iss. 20 — 11 November 2016

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