搜索

x

留言板

姓名
邮箱
手机号码
标题
留言内容
验证码

downloadPDF
引用本文:
Citation:

    赵国涛, 王立夫, 关博飞

    A class of edge set affecting network controllability

    Zhao Guo-Tao, Wang Li-Fu, Guan Bo-Fei
    PDF
    HTML
    导出引用
    • 应用复杂网络描述大规模复杂系统间的相互作用已被广泛接受, 网络中某些边遭受攻击或破坏会使网络不能控. 然而哪些边失效后会对网络能控性造成影响? 针对这一问题, 本文首先提出了类关键边集的概念, 并给出了类关键边集的判定定理. 然后通过建立类关键边集失效模型, 来研究类关键边集失效对网络能控性的影响. 最后将类关键边集失效、随机失效、按度失效和按介数失效进行对比, 验证了无论是在模型网络(ER随机网络、BA无标度网络、随机三角形网络和随机矩形网络), 还是26种不同领域的实际网络中, 类关键边集失效对网络能控性的破坏力最大, 同时该结果为网络边攻击提供了一种新方法.
      It is undisputed that complex networks are used to describe the interaction between large-scale complex systems. Different edges have different effects on network controllability. When some edges in a network are attacked or destroyed, the network controllability may be affected very little; when some other edges are attacked, network controllability may be affected very greatly, even results in the uncontrollability of the network. Which edges failure will affect the network controllability? To solve this problem, according to the node classification and edge classification, the concept of quasi-critical edge set is proposed, and the judgment theorem of quasi-critical edge set is given in this paper. In order to study the influence of quasi-critical edge set on the network controllability, the failure model of quasi-critical edge set is proposed, and the network controllability is quantified by the ratio of the number of driver nodes to the number of network nodes. In this failure model, the quasi-critical edge set with the minimum number of edges is removed first, thus destroying the network controllability quickly. By analyzing the failure model of quasi-critical edge set, the failure curve of quasi-critical edge set is obtained. It is found that the failure curve is a piecewise linear function and that the maximum (initial) slope of failure curve is related to the average degree of network. In addition, the failure of quasi-critical edge set has the greatest influence on network controllability. A comparison among the failure of quasi-critical edge set, random failure, degree failure, and betweenness failure verifies that the failure of quasi-critical edge set has the greatest damage to the network controllability in both model networks (ER random network, BA scale-free network, random triangle network and random rectangle network) and real networks in 26 different fields. For some of real networks, such as cancer cell networks, terrorist communication networks and other networks that are harmful to human beings, the failure model of quasi-critical edge set can provide a reference attack method.
          通信作者:王立夫,wlfkz@qq.com
        • 基金项目:国家自然科学基金(批准号: 61573077, U1808205)、中央高校基本科研业务费专项资金(批准号: N2023022)和河北省自然科学基金(批准号: F2016501023, F2017501041) 资助的课题
          Corresponding author:Wang Li-Fu,wlfkz@qq.com
        • Funds:Project supported by the National Natural Science Foundation of China (Grant Nos. 61573077, U1808205), the Fundamental Research Fund for the Central Universities of Ministry of Education of China (Grant No. N2023022), and the Natural Science Foundation of Hebei Province, China (Grant Nos. F2016501023, F2017501041)
        [1]

        [2]

        [3]

        [4]

        [5]

        [6]

        [7]

        [8]

        [9]

        [10]

        [11]

        [12]

        [13]

        [14]

        [15]

        [16]

        [17]

        [18]

        [19]

        [20]

        [21]

        [22]

        [23]

        [24]

        [25]

        [26]

        [27]

        [28]

        [29]

        [30]

        [31]

        [32]

        [33]

        [34]

        [35]

        [36]

        [37]

        [38]

        [39]

        [40]

      • 网络 N L $n_{\rm D}$ 边移除比例$ p $后网络的$n_{\rm D}$
        p= 0.2 p= 0.5 p= 0.8
        随机 按度 按介数 FQ 随机 按度 按介数 FQ 随机 按度 按介数 FQ
        Electronic Circuits_S208 122 189 0.24 0.33 0.29 0.43 0.53 0.48 0.57 0.56 0.77 0.74 0.84 0.85 0.95
        Electronic Circuits_S402 252 399 0.23 0.32 0.30 0.42 0.53 0.52 0.56 0.57 0.77 0.76 0.84 0.84 0.95
        Electronic Circuits_S838 512 819 0.23 0.33 0.30 0.42 0.53 0.48 0.55 0.57 0.77 0.74 0.84 0.84 0.95
        Animal_Hens 32 496 0.03 0.03 0.25 0.19 0.44 0.03 0.59 0.34 0.69 0.19 0.81 0.63 0.88
        Collaboration_in jazz 198 5484 0.01 0.01 0.01 0.14 0.43 0.03 0.02 0.32 0.72 0.08 0.38 0.60 0.91
        Joint senate press releases 92 954 0.01 0.01 0.01 0.22 0.48 0.07 0.01 0.42 0.76 0.27 0.36 0.53 0.92
        Questionnaire for high tech managers_Advice 21 190 0.05 0.05 0.14 0.19 0.43 0.10 0.38 0.43 0.67 0.29 0.62 0.67 0.86
        Questionnaire for high tech managers_Friendship 21 102 0.10 0.19 0.14 0.33 0.52 0.24 0.43 0.67 0.76 0.57 0.71 0.86 0.90
        Questionnaire for high tech managers_Reports 21 20 0.76 0.76 0.81 0.81 0.81 0.76 0.81 0.81 0.90 0.86 0.86 0.86 0.95
        corporate law partnership_law firm 71 892 0.01 0.03 0.04 0.20 0.46 0.06 0.20 0.31 0.73 0.25 0.56 0.65 0.90
        Children's network of friendship_Third grade 22 177 0.05 0.05 0.05 0.18 0.36 0.05 0.27 0.27 0.64 0.36 0.68 0.64 0.86
        Children's network of friendship_Fourth grade 24 101 0.04 0.04 0.08 0.17 0.29 0.42 0.25 0.33 0.58 0.50 0.71 0.58 0.83
        Children's network of friendship_Fifth grade 22 103 0.05 0.05 0.09 0.23 0.36 0.18 0.23 0.41 0.68 0.50 0.64 0.73 0.86
        Questionnaire for bank_Advice-seeking 11 30 0.27 0.36 0.45 0.36 0.55 0.45 0.55 0.55 0.73 0.73 0.73 0.73 0.91
        Questionnaire for bank_Satisfying 11 51 0.18 0.27 0.27 0.36 0.55 0.36 0.36 0.55 0.73 0.64 0.73 0.64 0.82
        Questionnaire for bank_Confiding 11 27 0.18 0.27 0.27 0.36 0.55 0.36 0.45 0.55 0.73 0.64 0.82 0.82 0.91
        Questionnaire for bank_Close-friends 11 20 0.36 0.45 0.36 0.45 0.55 0.55 0.64 0.54 0.82 0.82 0.82 0.73 0.91
        Trade goods in different countries_Foods 24 307 0.04 0.04 0.08 0.21 0.38 0.04 0.17 0.33 0.67 0.17 0.67 0.58 0.88
        Trade goods in different countries_Crude materials 24 307 0.04 0.04 0.04 0.21 0.38 0.04 0.21 0.29 0.71 0.17 0.54 0.71 0.88
        Trade goods in different countries_Minerals 24 135 0.13 0.13 0.17 0.38 0.58 0.29 0.50 0.58 0.79 0.58 0.83 0.88 0.92
        Trade goods in different countries_Diplomacy 24 369 0.04 0.04 0.04 0.21 0.29 0.04 0.12 0.33 0.58 0.12 0.63 0.75 0.83
        Questionnaire for grade seven students_Get on 29 361 0.03 0.03 0.03 0.21 0.34 0.03 0.10 0.34 0.65 0.10 0.52 0.59 0.90
        Questionnaire for grade seven students_Best friends 29 181 0.03 0.03 0.03 0.17 0.45 0.14 0.21 0.45 0.72 0.48 0.59 0.62 0.93
        Questionnaire for grade seven students_Work with 29 198 0.03 0.07 0.10 0.21 0.45 0.21 0.21 0.41 0.72 0.41 0.59 0.62 0.90
        Friendships among high school boys_1957 73 243 0.18 0.25 0.19 0.29 0.53 0.34 0.34 0.49 0.77 0.63 0.67 0.78 0.92
        Friendships among high school boys_1958 73 263 0.15 0.19 0.15 0.25 0.52 0.29 0.27 0.47 0.77 0.55 0.64 0.78 0.93
        下载: 导出CSV
      • [1]

        [2]

        [3]

        [4]

        [5]

        [6]

        [7]

        [8]

        [9]

        [10]

        [11]

        [12]

        [13]

        [14]

        [15]

        [16]

        [17]

        [18]

        [19]

        [20]

        [21]

        [22]

        [23]

        [24]

        [25]

        [26]

        [27]

        [28]

        [29]

        [30]

        [31]

        [32]

        [33]

        [34]

        [35]

        [36]

        [37]

        [38]

        [39]

        [40]

      • [1] 孔江涛, 黄健, 龚建兴, 李尔玉.基于复杂网络动力学模型的无向加权网络节点重要性评估. 必威体育下载 , 2018, 67(9): 098901.doi:10.7498/aps.67.20172295
        [2] 韩忠明, 陈炎, 李梦琪, 刘雯, 杨伟杰.一种有效的基于三角结构的复杂网络节点影响力度量模型. 必威体育下载 , 2016, 65(16): 168901.doi:10.7498/aps.65.168901
        [3] 侯绿林, 老松杨, 肖延东, 白亮.复杂网络可控性研究现状综述. 必威体育下载 , 2015, 64(18): 188901.doi:10.7498/aps.64.188901
        [4] 韩忠明, 吴杨, 谭旭升, 段大高, 杨伟杰.面向结构洞的复杂网络关键节点排序. 必威体育下载 , 2015, 64(5): 058902.doi:10.7498/aps.64.058902
        [5] 王亚奇, 王静, 杨海滨.基于复杂网络理论的微博用户关系网络演化模型研究. 必威体育下载 , 2014, 63(20): 208902.doi:10.7498/aps.63.208902
        [6] 袁铭.带有层级结构的复杂网络级联失效模型. 必威体育下载 , 2014, 63(22): 220501.doi:10.7498/aps.63.220501
        [7] 刘金良.具有随机节点结构的复杂网络同步研究. 必威体育下载 , 2013, 62(4): 040503.doi:10.7498/aps.62.040503
        [8] 丁益民, 丁卓, 杨昌平.基于社团结构的城市地铁网络模型研究. 必威体育下载 , 2013, 62(9): 098901.doi:10.7498/aps.62.098901
        [9] 胡枫, 赵海兴, 何佳倍, 李发旭, 李淑玲, 张子柯.基于超图结构的科研合作网络演化模型. 必威体育下载 , 2013, 62(19): 198901.doi:10.7498/aps.62.198901
        [10] 高湘昀, 安海忠, 方伟.基于复杂网络的时间序列双变量相关性波动研究. 必威体育下载 , 2012, 61(9): 098902.doi:10.7498/aps.61.098902
        [11] 柳爽, 吕翎, 李钢.一类不确定复杂网络的滑模追踪同步. 必威体育下载 , 2012, 61(16): 160507.doi:10.7498/aps.61.160507
        [12] 吕翎, 柳爽, 张新, 朱佳博, 沈娜, 商锦玉.节点结构互异的复杂网络的时空混沌反同步. 必威体育下载 , 2012, 61(9): 090504.doi:10.7498/aps.61.090504
        [13] 周漩, 张凤鸣, 周卫平, 邹伟, 杨帆.利用节点效率评估复杂网络功能鲁棒性. 必威体育下载 , 2012, 61(19): 190201.doi:10.7498/aps.61.190201
        [14] 周漩, 张凤鸣, 李克武, 惠晓滨, 吴虎胜.利用重要度评价矩阵确定复杂网络关键节点. 必威体育下载 , 2012, 61(5): 050201.doi:10.7498/aps.61.050201
        [15] 崔爱香, 傅彦, 尚明生, 陈端兵, 周涛.复杂网络局部结构的涌现:共同邻居驱动网络演化. 必威体育下载 , 2011, 60(3): 038901.doi:10.7498/aps.60.038901
        [16] 邢长明, 刘方爱.基于Sierpinski分形垫的确定性复杂网络演化模型研究. 必威体育下载 , 2010, 59(3): 1608-1614.doi:10.7498/aps.59.1608
        [17] 熊菲, 刘云, 司夏萌, 丁飞.基于Web 2.0的边与节点同时增长网络模型. 必威体育下载 , 2010, 59(10): 6889-6895.doi:10.7498/aps.59.6889
        [18] 吕翎, 张超.一类节点结构互异的复杂网络的混沌同步. 必威体育下载 , 2009, 58(3): 1462-1466.doi:10.7498/aps.58.1462
        [19] 郭进利.新节点的边对网络无标度性影响. 必威体育下载 , 2008, 57(2): 756-761.doi:10.7498/aps.57.756
        [20] 李 季, 汪秉宏, 蒋品群, 周 涛, 王文旭.节点数加速增长的复杂网络生长模型. 必威体育下载 , 2006, 55(8): 4051-4057.doi:10.7498/aps.55.4051
      计量
      • 文章访问数:3623
      • PDF下载量:63
      • 被引次数:0
      出版历程
      • 收稿日期:2020-11-03
      • 修回日期:2020-12-30
      • 上网日期:2021-07-07
      • 刊出日期:2021-07-20

        返回文章
        返回
          Baidu
          map