Dynamic behaviors of disaster spreading in directed scale free networks

Gaoxia Wang, Jianmin Dai, Yi Shen, Enjie Luan

Research output: Contribution to journalArticle

Abstract

Dynamic model of disaster spreading on directed networks is discussed. The end behavior of model evolvement is divided into three scenarios: System stable, fluctuate, and breakdown. Using the node recovery ratio as the measures to evaluate the level of disaster spreading, by means of simulations, the dynamics behaviors of disaster spreading on directed scale-free networks with tunable exponents is explored. The impact of the important parameters, such as recovery factor, threshold of nodes on dynamics behaviors of disaster spreading is discussed. For the recovery factor, there exist two critical thresholds corresponding to the transition of three scenarios, the larger the exponents are, the lighter the level of disaster is. Finally, the control strategy based on hub weights is presented.

Original languageEnglish (US)
Pages (from-to)83-85
Number of pages3
JournalHuazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition)
Volume37
Issue number3
StatePublished - Mar 1 2009
Externally publishedYes

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Complex networks
Disasters
Recovery
Dynamic models

Keywords

  • Disaster spreading
  • Dynamic behavior
  • Models
  • Scale-free networks
  • Tunable exponents

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

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AB - Dynamic model of disaster spreading on directed networks is discussed. The end behavior of model evolvement is divided into three scenarios: System stable, fluctuate, and breakdown. Using the node recovery ratio as the measures to evaluate the level of disaster spreading, by means of simulations, the dynamics behaviors of disaster spreading on directed scale-free networks with tunable exponents is explored. The impact of the important parameters, such as recovery factor, threshold of nodes on dynamics behaviors of disaster spreading is discussed. For the recovery factor, there exist two critical thresholds corresponding to the transition of three scenarios, the larger the exponents are, the lighter the level of disaster is. Finally, the control strategy based on hub weights is presented.

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