Robustness analysis of the complex network

Mingxin Liang, Fanzhen Liu, Chao Gao*, Zili Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of 2017 IEEE 6th Data Driven Control and Learning Systems Conference (DDCLS'17)
EditorsMingxuan Sun, Huijun Gao
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages638-643
Number of pages6
ISBN (Electronic)9781509054619, 9781509054596
ISBN (Print)9781509054626
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event6th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2017 - Chongqing, China
Duration: 26 May 201727 May 2017

Conference

Conference6th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2017
Country/TerritoryChina
CityChongqing
Period26/05/1727/05/17

Keywords

  • Complex Network
  • Robustness
  • Propagation
  • Centrality
  • Node Ranking

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