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Using Proxies for Node Immunization Identification on Large Graphs
DOI:10.1109/ACCESS.2017.2723838.png)
摘要
En 中文
Given a large graph, like a social network, which k nodes should be immunized (or removed) to make the network safe from the spread of a virus? This is the node immunization problem. One of the classical methods, inspired by immunology, in analyzing this problem relies on the calculation of the largest eigenvalue before and after immunization in order to create the largest difference in eigenvalue. We propose a method that does not rely on a costly calculation of eigenvalues; instead, we rely on the notion of proxies and deterministic routing areas in order to find such nodes to immunize. We show that our results are consistent with the notion of vulnerability and produces equivalent results when compared with the existing algorithms. Furthermore, experimental results show that when a virus is not allowed to die out (controlled by the strength of the virus), our algorithm ensures that more nodes are safe from infection.
Keyword:
Immunization
linear time
proxies
tree-graph
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期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
An Efficient Algorithm for Nonlinear Model Predictive Control of Large-Scale Systems Part I: Description of the Method (Ein effizienter Algorithmus für die nichtlineare prädiktive Regelung großer Systeme Teil I: Methodenbeschreibung)大型系统非线性模型预测控制的有效算法第一部分: 方法的描述 (Ein effizienter algorithms f ü r die nichtlineare pr ä diktive Regelung gro ß er Systeme Teil I: Methodenbeschreibung)
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