Hayastan Shakarian切割：测量网络断开的影响
The Hayastan Shakarian cut: measuring the impact of network disconnections
摘要：
在这篇文章中，我们提出了Hayastan Shakarian（HS），一个复杂网络的鲁棒性指标。HS测量网络断开（边缘）的影响，同时比较剩余连接组件的大小。严格地说，Hayastan Shakarian指数被定义为边缘去除，其产生最大连通分量的大小除以其余分量的大小之和的最大倒数。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。我们考虑使用Hayastan Shakarian切割（用最大HS断开边缘）和其他众所周知的策略作为更高介数中心性断开。所有的策略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，基于断开使用Hayastan Shakarian切割的攻击比基于其他中心性措施的相同攻击更危险（降低鲁棒性）。我们认为，Hayastan Shakarian cut以及其他基于最大连通分量大小的度量，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 the Hayastan Shakarian (HS), a robustness index for complex networks. HS measures the impact of a network disconnection (edge) while comparing the sizes of the remaining connected components. Strictly speaking, the Hayastan Shakarian index is defined as edge removal that produces the maximal 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 using the Hayastan Shakarian cut (disconnecting the edge with max HS) and other well-known strategies as the higher betweenness centrality disconnection. All strategies were compared regarding the behavior of the robustness (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 using the Hayastan Shakarian cut are more dangerous (decreasing the robustness) than the same attacks based on other centrality measures. We believe that the Hayastan Shakarian cut, 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.
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