基于极大连通子图边界的复杂网络恢复研究

doi:10.16182/j.issn1004731x.joss.20-FZ0295

系统仿真学报 ›› 2020, Vol. 32 ›› Issue (12): 2306-2316.doi: 10.16182/j.issn1004731x.joss.20-FZ0295

基于极大连通子图边界的复杂网络恢复研究

王哲^1,2, 李建华¹, 康东^1,2

1.空军工程大学信息与导航学院,陕西西安 710077;
2.国防科技大学信息通信学院,陕西西安 710100

收稿日期:2020-03-25 修回日期:2020-08-11 出版日期:2020-12-18 发布日期:2020-12-16
作者简介:王哲(1985-),男,陕西延安,博士生,讲师,研究方向为复杂系统建模与分析;李建华(1965-),男,陕西白水,博士,教授,博导,研究方向为空天信息作战。
基金资助:
国防科技战略先导计划(19-ZLXD-04-11-01-100-01)

Research on Recovering of Complex Networks Based on Boundary Nodes of Giant Connected Component

Wang Zhe^1,2, Li Jianhua¹, Kang Dong^1,2

1. Information and Navigation College,Air Force Engineering University,Xi'an 710077,China;
2. College of Information and Communication,National University of Defense Technology,Xi'an 710100,China

Received:2020-03-25 Revised:2020-08-11 Online:2020-12-18 Published:2020-12-16

摘要/Abstract

摘要： 网络恢复是应对不可避免的故障或失效的重要途径,合理的恢复策略有助于降低资源损耗且提高网络鲁棒性能。为研究复杂网络恢复动力学行为及其与网络鲁棒性之间关系,构建了基于极大连通子图边界的复杂网络恢复模型(Recovery Model of Boundary Nodes,RMBN),设计了网络平均恢复(Average Recovery of Boundary Nodes,ARBN)和择优恢复(Priority Recovery of Boundary Nodes,PRBN)策略。不同恢复策略在3种网络模型上的仿真结果表明,随着恢复比例的增大,网络鲁棒性逐渐增强且恢复作用时间更早、恢复能力更强,为复杂网络拓扑结构设计与鲁棒性优化提供借鉴。

关键词: 复杂网络, 鲁棒性, 恢复模型, 恢复策略

Abstract: Network recovery is an important way to solve the inevitable failure,and the reasonable recovery strategy can reduce the cost of resource and improve the network robustness.In order to study the dynamic behavior of recovery process and the relationship between recovery and network robustness,a Recovery Model of Boundary Nodes (RMBN) based on boundary of giant connected component is proposed,and two network Recovery strategies,Average Recovery of Boundary Nodes (ARBN) strategy and Priority Recovery of Boundary Nodes (PRBN) strategy are designed.The simulation results of different recovery strategies on three network models show that with the increase of recovery ratio,the network robustness is gradually enhanced,the recovery strategy takes effect earlier and the recovery capability becomes stronger,which may provide reference for the design of network topology and optimization of system robustness.

Key words: complex network, robustness, recovery model, recovery strategy

中图分类号:

TP391

王哲, 李建华, 康东. 基于极大连通子图边界的复杂网络恢复研究[J]. 系统仿真学报, 2020, 32(12): 2306-2316.

Wang Zhe, Li Jianhua, Kang Dong. Research on Recovering of Complex Networks Based on Boundary Nodes of Giant Connected Component[J]. Journal of System Simulation, 2020, 32(12): 2306-2316.

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基于极大连通子图边界的复杂网络恢复研究

Research on Recovering of Complex Networks Based on Boundary Nodes of Giant Connected Component

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