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Entropy Optimization of Scale-free Networks Robustness to Targeted Attack

机译：无标度网络鲁棒性针对性攻击的熵优化

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摘要

Many networks are characterized by highly heterogeneous distributions of links which are called scale-free networks, with the degree distributions following p(k)~ck~(-α). Entropy of the degree distribution has been proved an average measure for the network heterogeneity so can be useful for optimizing scale-free network robustness to random failure. In this work we improve the theory of the effectiveness of entropy of the degree distribution on measuring scale-free networks robustness to targeted attack, by introducing the edges related parameter of pd which means the ratio threshold of the lost edges to all the edges in the topology at which the scale-free networks will break down. Our work has proved that the entropy of the degree distribution is really an effective measurement for network robustness to not only random failure but also targeted attack.
机译：许多网络的特征是链路的高度异构分布，称为无标度网络，其度分布遵循p（k）〜ck〜（-α）。事实证明，度分布的熵是网络异构性的平均度量，因此对于优化无标度网络对随机故障的鲁棒性很有用。在这项工作中，我们通过引入pd的边缘相关参数（即丢失边缘与边缘中所有边缘的比率阈值），改进了度分布的熵对测量无标度网络对目标攻击的鲁棒性的有效性的理论。无标度网络将崩溃的拓扑。我们的工作证明，度分布的熵确实是衡量网络鲁棒性的有效方法，它不仅针对随机故障，而且针对目标攻击。

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