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复杂网络中心性对灾害蔓延的影响

李泽荃 张瑞新 杨曌 赵红泽 于健浩

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复杂网络中心性对灾害蔓延的影响

李泽荃, 张瑞新, 杨曌, 赵红泽, 于健浩

Influence complex network centrality on disaster spreading

Li Ze-Quan, Zhang Rui-Xin, Yang Zhao, Zhao Hong-Ze, Yu Jian-Hao
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  • 基于一个普适性的灾害蔓延动力学模型,在三种网络拓扑结构(随机网、小世界网和无标度网)下,仿真分析了网络中心性对灾害蔓延速度和扩散趋势的影响. 通过改变初始蔓延条件来分析网络初始状态对蔓延效率的影响, 并着重讨论了在四种初始崩溃节点选取策略下灾害蔓延最终状态的差异. 结果表明: 对于四种攻击策略, 网络最终状态有着明显的差异,网络对随机攻击具有较强的抵御能力,而对于目标, 攻击却显示较强的脆弱性,或许,三种网络表现出不同的脆弱程度. 最后,在一个实际网络上对理论分析结果进行了验证.
    Based on a general dynamical model for disaster spreading, in different network structures, i.e. in Erdos-Renyi network, scale-free network and small world network, the influences of network centrality on the speed and trend of disaster spreading are analyzed by simulation. By changing the initial spreading condition, the influence of initial state on the spreading efficiency is analyzed. In this paper the differences between final disaster spreading state are mainly discussed based on four initial vertex-choosing strategies. For the four strategies, it is shown that there are apparent differences. Complex network has a strong ability to resist random attacks but is is fragile to resist intentional attacks. However, the three networks show different degrees of fragility. And then, the theoretical analysis results are verified in an actual network.
    • 基金项目: 国家自然科学基金(批准号: 91024029)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 91024029).
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    Watts D J, Strogatz S H 1998 Nature 440 442

    [2]

    Barabasi A L, Albert R 1999 Science 509 512

    [3]

    Albert R, Barabasi A L 2002 Rev. Mod. Phys. 74 47

    [4]

    Steven H, Strogatz 2001 Nature 410 268

    [5]

    Bianconi G, Barabasi A L 2001 Phys. Rev. Lett. 86 5635

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    Valentini L, Perugini D, Poli G 2007 Physica A 377 323

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    Lambiotte R, Blonel V D, de Kerchove C, Huens E, Prieur C, Smoreda Z, Dooren P V 2008 arXiv:0802.2178

    [8]

    Drossel B, McKane A 2003 Handbook of Graphs and Networks (Berlin: Jclin Wiley and Sons)

    [9]

    Beggs J M, Plenz D 2003 Journal of Neuroscience 23 11167

    [10]

    Buzna L, Peters K, Helbing D 2006 Physica. A 363 132

    [11]

    Goyal S 2007 Connections: An Introduction to the Economics of Networks (Princeton: Princeton University)

    [12]

    Ormerod P, Roach A P 2004 Physica A 339 645

    [13]

    Helbing D, Kuhnert C 2003 Physica A 328 584

    [14]

    Weng W G, Ni S J, Shen S F, Yuan H Y 2007 Acta Phys. Sin. 55 1943 (in Chinese) [翁文国, 倪顺江, 申世飞, 袁宏永 2007 55 1938]

    [15]

    Zhang Z W, Tan X, Ouyang M 2011 J. Mat. Pra. Theo. 75 84 (in Chinese) [张振文, 谭欣, 欧阳敏 2011 数学的实践与认识 75 84]

    [16]

    Ouyang M, Fei Q, Yu M H 2008 Acta Phys. Sin. 56 6763 (in Chinese) [欧阳敏, 费奇, 余明晖 2008 56 6763]

    [17]

    Buzna L, Peters K, Hendrik A 2007 Phys. Rev. 107 114

    [18]

    David M P, Gary W F 2002 PNAS 4(3) 5211

    [19]

    He D R, Liu Z H, Wang B H 2008 Complex Systems and Complex Networks (Beijing: Higher Education Press) (in Chinese) [何大韧, 刘宗华, 汪秉宏 2008 复杂系统与复杂网络 (北京: 高等教育出版社)]

    [20]

    Chen G L 2008 Adva. Mech. 6 53 [陈光荣2008力学进展 653 662]

    [21]

    Pan Q D 2011 Ph. D. Dissertation (Beijing: China University of Mining and Technology) (in Chinese) [潘启东 2011 博士学位论文 (北京: 中国矿业大学)]

    [22]

    Barabasi A L 2003 Linked: How Everything Is Connected to Everything Else and What it Means (New York: The Penguin Group)

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计量
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  • PDF下载量:  1013
  • 被引次数: 0
出版历程
  • 收稿日期:  2012-04-28
  • 修回日期:  2012-06-18
  • 刊出日期:  2012-12-05

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