Robustness Analysis of the Complex Network

被引:0
|
作者
Liang, Mingxin [1 ]
Liu, Fanzhen [1 ]
Gao, Chao [1 ,2 ,3 ]
Zhang, Zili [1 ,4 ]
机构
[1] Southwest Univ, Sch Comp & Informat Sci, Chongqing 400715, Peoples R China
[2] Potsdam Inst Climate Impact Res PIK, D-14473 Potsdam, Germany
[3] Humboldt Univ, Inst Phys, D-12489 Berlin, Germany
[4] Deakin Univ, Sch Informat Technol, Locked Bag 20000, Geelong, Vic 3220, Australia
来源
2017 6TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS (DDCLS) | 2017年
基金
中国国家自然科学基金;
关键词
Complex Network; Robustness; Propagation; Centrality; Node Ranking;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The robustness is one of the primary characteristics of a real system, which impacts the function and performance of the system. Many real systems in our real world can be formulated as complex networks. It is a feasible method to estimate the robustness of real systems from the perspective of complex networks. The robustness evaluation is one of the basic and hot research topics in the field of complex networks. This paper presents a network-based simulation platform for analyzing and evaluating the robustness of a real system in terms of existing famous measurements. Furthermore, some experiments are implemented in networks with various topologies and scales under the conditions of different types of attacks. The results show that the structural topology is the major factor in the robustness of a network. And malicious attacks result in more damages than random attacks. And there is a correlation among different attack patterns based on various vertex centralities.
引用
收藏
页码:638 / 643
页数:6
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