2009 Volume 18 Issue 3
Article Contents

Cui Di, Gao Zi-You, Zheng Jian-Feng. 2009: Tolerance of edge cascades with coupled map lattices methods, Chinese Physics B, 18(3): 992-996.
Citation: Cui Di, Gao Zi-You, Zheng Jian-Feng. 2009: Tolerance of edge cascades with coupled map lattices methods, Chinese Physics B, 18(3): 992-996.

Tolerance of edge cascades with coupled map lattices methods

  • Available Online: 30/03/2009
  • Fund Project: National Basic Research Program of China(Grant 2006CB705500)%Chang-Jiang Scholars and Innovative Research Team in University of China(Grant IRT0605)%the National Natural Science Foundation of China(Grant 70631001)
  • This paper studies the cascading failure on random networks and scale-free networks by introducing the tolerance parameter of edge based on the coupled map lattices methods. The whole work focuses on investigating some indices including the number of failed edges, dynamic edge tolerance capacity and the perturbation of edge. In general, it assumes that the perturbation is attributed to the normal distribution in adopted simulations. By investigating the effectiveness of edge tolerance in scale-free and random networks, it finds that the larger tolerance parameter 位 can more efficiently delay the cascading failure process for scale-free networks than random networks. These results indicate that the cascading failure process can be effectively controlled by increasing the tolerance parameter A. Moreover, the simulations also show that, larger variance of perturbation can easily trigger the cascading failures than the smaller one. This study may be useful for evaluating efficiency of whole traffic systems, and for alleviating cascading failure in such systems.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Tolerance of edge cascades with coupled map lattices methods

Abstract: This paper studies the cascading failure on random networks and scale-free networks by introducing the tolerance parameter of edge based on the coupled map lattices methods. The whole work focuses on investigating some indices including the number of failed edges, dynamic edge tolerance capacity and the perturbation of edge. In general, it assumes that the perturbation is attributed to the normal distribution in adopted simulations. By investigating the effectiveness of edge tolerance in scale-free and random networks, it finds that the larger tolerance parameter 位 can more efficiently delay the cascading failure process for scale-free networks than random networks. These results indicate that the cascading failure process can be effectively controlled by increasing the tolerance parameter A. Moreover, the simulations also show that, larger variance of perturbation can easily trigger the cascading failures than the smaller one. This study may be useful for evaluating efficiency of whole traffic systems, and for alleviating cascading failure in such systems.

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