Literature DB >> 27886508

Immunization and Targeted Destruction of Networks using Explosive Percolation.

Pau Clusella1,2, Peter Grassberger1,3, Francisco J Pérez-Reche1, Antonio Politi1.   

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.

Entities:  

Mesh:

Year:  2016        PMID: 27886508     DOI: 10.1103/PhysRevLett.117.208301

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  9 in total

1.  Detecting and modelling real percolation and phase transitions of information on social media.

Authors:  Jiarong Xie; Fanhui Meng; Jiachen Sun; Xiao Ma; Gang Yan; Yanqing Hu
Journal:  Nat Hum Behav       Date:  2021-04-01

2.  Fast and simple decycling and dismantling of networks.

Authors:  Lenka Zdeborová; Pan Zhang; Hai-Jun Zhou
Journal:  Sci Rep       Date:  2016-11-29       Impact factor: 4.379

3.  Optimal percolation on multiplex networks.

Authors:  Saeed Osat; Ali Faqeeh; Filippo Radicchi
Journal:  Nat Commun       Date:  2017-11-16       Impact factor: 14.919

4.  Systematic comparison between methods for the detection of influential spreaders in complex networks.

Authors:  Şirag Erkol; Claudio Castellano; Filippo Radicchi
Journal:  Sci Rep       Date:  2019-10-22       Impact factor: 4.379

5.  Optimization of targeted node set in complex networks under percolation and selection.

Authors:  Yang Liu; Xi Wang; Jürgen Kurths
Journal:  Phys Rev E       Date:  2018-07       Impact factor: 2.529

6.  Fundamental difference between superblockers and superspreaders in networks.

Authors:  Filippo Radicchi; Claudio Castellano
Journal:  Phys Rev E       Date:  2017-01-18       Impact factor: 2.529

7.  Characteristic functional cores revealed by hyperbolic disc embedding and k-core percolation on resting-state fMRI.

Authors:  Wonseok Whi; Youngmin Huh; Seunggyun Ha; Hyekyoung Lee; Hyejin Kang; Dong Soo Lee
Journal:  Sci Rep       Date:  2022-03-22       Impact factor: 4.379

8.  Universal mechanism for hybrid percolation transitions.

Authors:  Deokjae Lee; Wonjun Choi; J Kertész; B Kahng
Journal:  Sci Rep       Date:  2017-07-18       Impact factor: 4.379

9.  Rapid decay in the relative efficiency of quarantine to halt epidemics in networks.

Authors:  Giovanni Strona; Claudio Castellano
Journal:  Phys Rev E       Date:  2018-02       Impact factor: 2.529

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.