| 考虑社群结构的复杂网络的级联故障抵制模型 |
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| 引用本文： | 陆靖桥,傅秀芬,蒙在桥.考虑社群结构的复杂网络的级联故障抵制模型[J].广东工业大学学报,2016,33(5):22-27. |
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| 作者姓名： | 陆靖桥 傅秀芬 蒙在桥 |
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| 作者单位： | 1.广东工业大学 计算机学院,广东 广州,510006;2.中山大学 信息科学与技术学院,广东 广州,510006 |
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| 基金项目： | 广东省科技计划项目（2012B091000173）;广东省自然科学基金资助项目（10451009001004804） |
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| 摘 要： | 研究复杂网络的级联故障对评估网络系统的稳定性具有重大意义.在经典的线性负载容量模型基础上,通过探测网络的社群结构,有选择地对社群边界节点的容量附加二次容忍值,建立级联故障抵制模型.在级联故障仿真中,采用不同干扰策略对IEEE118标准电网、国内现实电网等模拟故障过程.仿真结果表明,所建抵制模型通过对社群边界节点的容量进行二次扩容,能以较小的成本提高网络的稳定性,同时发现社群边界节点具备“防火墙”和“引爆点”的双重功能.通过将单一网络推广到两层耦合网络,发现在成本可控下新模型对相依网络的级联故障依然具备较好的抵制能力,说明本文所提模型具备一定的适应性.
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| 关 键 词： | 社群结构 复杂网络 级联故障 相依网络 |
| 收稿时间： | 2015-08-31 |
A Cascading Failure Resisting Model in Complex Networks Considering Community Structure |
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| LU Jing-qiao,FU Xiu-fen,MENG Zai-qiao.A Cascading Failure Resisting Model in Complex Networks Considering Community Structure[J].Journal of Guangdong University of Technology,2016,33(5):22-27. |
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| Authors: | LU Jing-qiao FU Xiu-fen MENG Zai-qiao |
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| Affiliation: | 1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China;;
2. School of Information Science and Technology, Sun Yat sen University, Guangzhou 510006, China |
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| Abstract: | Cascading failures in complex networks is of great significance for the stability assessment of complex networks. Based on the classical linear load and capacity model, a model resisting cascading failures is built by detecting the community structure of the networks and adding secondary tolerance value to community boundary nodes. In the process of cascading failures, different strategies are used to attack IEEE standard grids, domestic real grids. The simulation results show that the model can raise networks stability with lower cost by adding secondary tolerance value to community boundary nodes, finding that the community boundary nodes have the dual functions of "firewall" and "tipping point". By simulating the two-tier coupled networks except for single networks, the new model is also found abler to resist cascading failures in interdependent networks, which indicates that the proposed model has some flexibility. |
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| Keywords: | community structure complex networks cascading failures interdependent networks |
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