Percolation of interdependent networks with degree-correlated inter-connections
Percolation of interdependent networks with degree-correlated inter-connections
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DOI：
10.1088/1742-6596/574/1/012003
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发表时间：
2015-01
期刊：
影响因子：
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通讯作者：
A. Igarashi;Tomohiro Kuse
中科院分区：
文献类型：
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作者：
A. Igarashi;Tomohiro Kuse
在相互依赖的网络中，一个组成网络中的节点发生故障会导致另一个网络中的节点发生故障。这会递归地发生，并导致一连串的失败。众所周知，具有随机互联的相互依赖网络比单个网络具有更弱的稳健性。然而，如果相互依赖的网络像在实际情况中那样在构建它们的网络之间具有程度相关性，则相互依赖的网络的稳健性可能会改变。在本文中，我们对相互依赖的网络进行了数值模拟，得到了级联故障后的巨型簇大小，以评估其稳健性。我们证明了当一个相互依赖的网络具有正度相关时，它比无度相关的网络具有更强的稳健性。我们不仅给出了数值模拟结果，而且还给出了相互依赖网络的稳健性的理论结果。
In interdependent networks, failures of nodes in one constituent network lead nodes in another network to fail. This happens recursively and leads to a cascade of failures. It is known that the interdependent networks with random inter-connections have weaker robustness than the individual networks. However, if the interdependent networks have degree correlations between the networks constructing them as in the actual cases, the robustness of the interdependent networks may be changed. In this paper, we perform numerical simulations on interdependent networks and obtain the giant cluster sizes after the cascade of failures in order to evaluate the robustness. We show that when a interdependent network has a positive degree inter-correlation, it has the stronger robustness than that for the networks with no degree correlation. We show not only the numerical simulation results but theoretical ones for the robustness of the interdependent networks.