基于级联失效的有向无标度网络节点重要度评价模型

刘浩然; 王星淇; 邓玉静; 覃玉华

doi:10.11959/j.issn.1000-0801.2020042

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基于级联失效的有向无标度网络节点重要度评价模型

研究与开发 | 更新时间：2024-06-05

- 基于级联失效的有向无标度网络节点重要度评价模型
- Evaluation model of node importance in directed scale-free network based on cascade failure
- 电信科学 2020年36卷第2期页码：43-51
- 作者机构：
- 作者简介：
  
  [ "刘浩然（1980- ），男，博士，燕山大学博士生导师、信息科学与工程学院光电子工程系系副主任，主要研究方向为无线传感器网络、工业故障检测及预测" ]
  [ "王星淇（1994- ），男，燕山大学硕士生，主要研究方向为无线传感器网络" ]
  [ "邓玉静（1990- ），女，燕山大学博士生，主要研究方向为无线传感器网络" ]
  [ "覃玉华（1996- ），男，燕山大学硕士生，主要研究方向为无线传感器网络" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2020042
  中图分类号： TP393,TP212
- 网络出版日期：2020-02，
  
  纸质出版日期：2020-02-20
- 稿件说明：
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刘浩然, 王星淇, 邓玉静, 等. 基于级联失效的有向无标度网络节点重要度评价模型[J]. 电信科学, 2020,36(2):43-51.

Haoran LIU, Xingqi WANG, Yujing DENG, et al. Evaluation model of node importance in directed scale-free network based on cascade failure[J]. Telecommunications science, 2020, 36(2): 43-51.
刘浩然, 王星淇, 邓玉静, 等. 基于级联失效的有向无标度网络节点重要度评价模型[J]. 电信科学, 2020,36(2):43-51. DOI： 10.11959/j.issn.1000-0801.2020042.

Haoran LIU, Xingqi WANG, Yujing DENG, et al. Evaluation model of node importance in directed scale-free network based on cascade failure[J]. Telecommunications science, 2020, 36(2): 43-51. DOI： 10.11959/j.issn.1000-0801.2020042.

摘要

为了准确评价有向无标度网络中节点的重要度大小，从而更好地实施保护策略，提高网络抗毁性。考虑网络发生级联失效前后，节点负载量和网络连通性的变化情况，提出一种基于级联失效的有向无标度网络节点重要度评价模型。首先建立有向网络级联失效模型，推导出节点失效前承担的负载量，然后结合节点负载与其在数据传输过程中的位置因素，构建节点重要度评价模型。实验结果表明，在网络遭受选择性攻击时，采用该模型测得的关键节点失效后，分离生成子图数量和网络稳健性的变化趋势更明显，为具体应用提供实验数据。

Abstract

In order to evaluate the importance of nodes in a directed scale-free network accurately

the protection strategy can be better implemented and the destruction resistance of the network can be improved.Considering the changes of node load and network connectivity before and after cascading failure

a directed scale-free network node importance evaluation model based on cascading failure was proposed.Firstly

a cascading failure model of directed network was established to deduce the load of nodes before failure.Then

a node importance evaluation model was constructed by combining the node load and its location during data transmission.Experimental results show that when the network is attacked selectively

the number of generated sub-graphs and the network robustness change more obviously after the failure of key nodes measured by the model

providing experimental data for specific applications.

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Keywords

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