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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 453689, 13 pages
Research Article

Cascading Dynamics of Heterogenous Scale-Free Networks with Recovery Mechanism

1College of Mathematics and Information Science, Shandong Institute of Business and Technology, Yantai, Shandong 264005, China
2School of Computer Science, National University of Defense Technology, Changsha, Hunan 410073, China
3Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan 250022, China
4Information Security Center, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876, China
5National Computer Network Emergency Response Technical Team/Coordination Center, Beijing 100029, China

Received 11 November 2013; Accepted 6 December 2013

Academic Editor: Shuping He

Copyright © 2013 Shudong Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In network security, how to use efficient response methods against cascading failures of complex networks is very important. In this paper, concerned with the highest-load attack (HL) and random attack (RA) on one edge, we define five kinds of weighting strategies to assign the external resources for recovering the edges from cascading failures in heterogeneous scale-free (SF) networks. The influence of external resources, the tolerance parameter, and the different weighting strategies on SF networks against cascading failures is investigated carefully. We find that, under HL attack, the fourth kind of weighting method can more effectively improve the integral robustness of SF networks, simultaneously control the spreading velocity, and control the outburst of cascading failures in SF networks than other methods. Moreover, the third method is optimal if we only knew the local structure of SF networks and the uniform assignment is the worst. The simulations of the real-world autonomous system in, Internet have also supported our findings. The results are useful for using efficient response strategy against the emergent accidents and controlling the cascading failures in the real-world networks.