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中国物理学会期刊

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

CSTR: 32037.14.aps.67.20172295

Evaluation methods of node importance in undirected weighted networks based on complex network dynamics models

CSTR: 32037.14.aps.67.20172295
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  • 定量分析识别复杂网络中的重要节点对于研究复杂网络鲁棒性和脆弱性意义重大,当前基于网络结构的节点重要性评估方法成果丰富,而基于复杂网络动力学模型的节点重要性评估方法较少.针对无向加权网络,本文首先提出了构建其对应的复杂网络动力学模型的方法,并证明了该类复杂网络动力学模型是大范围内一致渐近稳定的;然后建立了复杂网络动力学模型的偏离均值和基于偏离均值的方差两级节点重要性评估标准;最后给出了扰动测试和破坏测试两种基于复杂网络动力学模型的节点重要性评估方法.基于复杂网络动力学模型的节点重要性评估方法不仅结合了网络拓扑结构信息,同时又结合了节点自身的特性,所以评价结果更为全面.将这两种方法用于ARPA (advanced research project agency)网络、对称无向加权网络、社交网络、Dobbs-Watts-Sabel网络和Barrat-Barthelemy-Vespignani网络的重要节点评估,并与已有的复杂网络节点重要性分析方法进行比较,证明了所提出方法的有效性.

     

    Identifying the most important nodes is significant for investigating the robustness and vulnerability of complex network. A lot of methods based on network structure have been proposed, such as degree, K-shell and betweenness, etc. In order to identify the important nodes in a more reasonable way, both the network topologies and the characteristics of nodes should be taken into account. Even at the same location, the nodes with different characteristics have different importance. The topological structures and the characteristics of the nodes are considered in the complex network dynamics model. However, such methods are rarely explored and their applications are restricted. In order to identify the important nodes in undirected weighted networks, in this paper we propose a method based on dynamics model. Firstly, we introduce a way to construct the corresponding dynamics model for any undirected weighted network, and the constructed model can be flexibly adjusted according to the actual situation. It is proved that the constructed model is globally asymptotic stable. To measure the changes of the dynamic model state, the mean deviation and the variance are presented, which are the criteria to evaluate the importance of the nodes. Finally, disturbance test and destructive test are proposed for identifying the most important nodes. Each node is tested in turn, and then the important nodes are identified. If the tested node can recover from the damaged state, the disturbance test is used. If the tested node is destroyed completely, the destructive test is used. The method proposed in this paper is based on the dynamics model. The node importance is influenced by the network topologies and the characteristics of nodes in these two methods. In addition, the disturbance test and destructive test are used in different situations, forming a complementary advantage. So the method can be used to analyze the node importance in a more comprehensive way. Experiments are performed on the advanced research project agency networks, the undirected networks with symmetric structures, the social network, the Dobbs-Watts-Sabel networks and the Barrat-Barthelemy-Vespignani networks. If the nodes in the network have the same dynamic model, the network is considered to be the homogeneous network; otherwise, the network is heterogeneous network. And experiments can be divided into four categories, namely, the disturbance test, the destructive test on the homogeneous network, the disturbance test and the destructive test on the heterogeneous network. The experimental results show that the methods proposed in this paper are effective and credible.

     

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