Miuz：测量断开节点连接的影响
Miuz: measuring the impact of disconnecting a node
摘要：
在这篇文章中，我们提出了Miuz，一个复杂网络的鲁棒性指标。Miuz测量从网络断开节点的影响，同时比较剩余连接组件的大小。严格地说，节点的Miuz定义为最大连通分量的大小除以其余连通分量的大小之和的倒数。我们在攻击策略中测试了我们的索引，其中节点以指定度量的降序断开连接。我们考虑了Miuz和其他著名的中心性度量，如介数、度和调和中心性。所有这些指标进行了比较的鲁棒性（R指数）在攻击过程中的行为。为了模拟互联网骨干网，攻击是在具有幂律度分布的复杂网络（无标度网络）中进行的。初步结果表明，基于断开几个节点Miuz的攻击比基于其他中心性措施的攻击更危险（降低鲁棒性）。我们相信，Miuz以及其他基于最大连通分量大小的度量方法，为复杂网络的其他鲁棒性度量提供了很好的补充。
英文摘要：
In this article we present Miuz, a robustness index for complex networks. Miuz measures the impact of disconnecting a node from the network while comparing the sizes of the remaining connected components. Strictly speaking, Miuz for a node is defined as the inverse of the size of the largest connected component divided by the sum of the sizes of the remaining ones. We tested our index in attack strategies where the nodes are disconnected in decreasing order of a specified metric. We considered Miuz and other well-known centrality measures such as betweenness, degree , and harmonic centrality. All of these metrics were compared regarding the behavior of the robust-ness (R-index) during the attacks. In an attempt to simulate the internet backbone, the attacks were performed in complex networks with power-law degree distributions (scale-free networks). Preliminary results show that attacks based on disconnecting a few number of nodes Miuz are more dangerous (decreasing the robustness) than the same attacks based on other centrality measures. We believe that Miuz, as well as other measures based on the size of the largest connected component, provides a good addition to other robustness metrics for complex networks.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
