基于節(jié)點冗余容量動態(tài)控制的復(fù)雜網(wǎng)絡(luò)魯棒性研究

張震; 劉迪洋; 張進; 謝記超

doi:10.11999/JEIT200185

基于節(jié)點冗余容量動態(tài)控制的復(fù)雜網(wǎng)絡(luò)魯棒性研究

doi: 10.11999/JEIT200185 cstr: 32379.14.JEIT200185

張震^1, ,,
劉迪洋¹,
張進²,
謝記超¹

1.
戰(zhàn)略支援部隊信息工程大學(xué) 鄭州 450000
2.
網(wǎng)絡(luò)通信與安全紫金山實驗室南京 210000

基金項目: 國家自然科學(xué)基金(61802429, 61872382, 61521003)，國家重點研發(fā)計劃(2017YFB0803201, 2017YFB0803204)

詳細信息

作者簡介:
張震：男，1986年生，講師，博士，碩士生導(dǎo)師，主要研究方向為主動防御、新型網(wǎng)絡(luò)體系架構(gòu)

劉迪洋：男，1995年生，碩士生，研究方向為復(fù)雜網(wǎng)絡(luò)魯棒性優(yōu)化、主動防御

張進：男，1979年生，工程師，博士，主要研究方向為寬帶信息網(wǎng)絡(luò)、網(wǎng)絡(luò)安全

謝記超：男，1993年生，碩士，助理研究員，研究方向為新型網(wǎng)絡(luò)體系結(jié)構(gòu)、網(wǎng)絡(luò)安全

通訊作者:
張震　zhangzhen2096@163.com

中圖分類號: TN919.2
計量
- 文章訪問數(shù): 1422
- HTML全文瀏覽量: 422
- PDF下載量: 85
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2020-03-20
- 修回日期: 2020-09-02
- 網(wǎng)絡(luò)出版日期: 2020-09-17
- 刊出日期: 2021-05-18

Research on the Robustness of Complex Networks Based on Dynamic Control of Node Redundancy Capacity

1.
PLA Strategic Support Force Information Engineering University, Zhengzhou 450000, China
2.
Network Communication and Security Purple Mountain Laboratory, Nanjing 210000, China

Funds: The National Natural Science Foundation of China(61802429, 61872382, 61521003), The National Key Research and Development Plan(2017YFB0803201, 2017YFB0803204)

摘要

摘要: 針對傳統(tǒng)級聯(lián)失效模型中冗余參數(shù)固定不變的問題，該文綜合考慮節(jié)點受攻擊程度不同和失效過程中網(wǎng)絡(luò)拓撲的動態(tài)變化，建立了基于節(jié)點冗余容量動態(tài)控制(DRC)的級聯(lián)失效模型。通過定義網(wǎng)絡(luò)相變臨界因子$\theta $衡量節(jié)點失效引發(fā)級聯(lián)失效的概率，分析了網(wǎng)絡(luò)魯棒性與$\theta $之間的相關(guān)性，并結(jié)合度分布函數(shù)詳細推導(dǎo)了$\theta $的解析表達式，基于解析表達式提出了兩種網(wǎng)絡(luò)魯棒性提升策略。仿真結(jié)果表明，在模型網(wǎng)絡(luò)和真實網(wǎng)絡(luò)中，根據(jù)被攻擊節(jié)點度的不同，通過調(diào)整節(jié)點初始負載參數(shù)$\tau $可以有效提高目標(biāo)網(wǎng)絡(luò)的魯棒性；DRC模型下級聯(lián)失效傳播范圍較Motter-Lai(ML)模型顯著減小。
- 復(fù)雜網(wǎng)絡(luò) /
- 級聯(lián)失效 /
- 網(wǎng)絡(luò)魯棒性 /
- 節(jié)點冗余容量
Abstract: In View of the problem of fixed redundancy parameters in the traditional cascade failure model, this paper comprehensively considers the different attack levels of nodes and the dynamic changes of the network topology during the failure process, and establishes a cascading failure model based on Dynamic control of node Redundancy Capacity (DRC). By defining the critical factor $\theta $ of the phase transition of the network to measure the probability of node failure leading to cascading failure, the correlation between network robustness and $\theta $ is analyzed, and the analytic expression of $\theta $ is derived in detail by combining degree distribution function, Based on analytic expressions, two network robustness enhancement strategies are proposed. The simulation results show that in model network and real network, the robustness of target network can be effectively improved by adjusting the initial load parameter $\tau $ of nodes according to the difference of degree of nodes under attack. The failure propagation range of DRC model is significantly reduced compared with Motter-Lai (ML) model.
- Complex networks /
- Cascade failure /
- Robustness /
- Node redundancy capacity

HTML全文

圖 1 BA網(wǎng)絡(luò)中$\theta $隨$\tau $變化圖

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圖 2 BA網(wǎng)絡(luò)ML模型中$\theta $隨$\alpha $變化圖

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圖 3 BA網(wǎng)絡(luò)DRC模型中$\theta $隨$\mu $變化圖

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圖 4 BA網(wǎng)絡(luò)中$R$隨$\theta $變化圖

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圖 5 BA網(wǎng)絡(luò)ML模型與DRC模型失效傳播對比圖

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圖 6 ARPA網(wǎng)絡(luò)拓撲

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圖 7 ARPA網(wǎng)絡(luò)中$\theta $隨$\tau $變化圖

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圖 8 ARPA網(wǎng)絡(luò)ML模型中$\theta $隨$\alpha $變化圖

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圖 9 ARPA網(wǎng)絡(luò)DRC模型中$\theta $隨$\mu $變化圖

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圖 10 ARPA網(wǎng)絡(luò)中$R$隨$\theta $變化圖

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圖 11 APRA網(wǎng)絡(luò)ML模型與DRC模型失效傳播對比圖

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