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Node Immunization with Time-Sensitive Restrictions

机译:具有时间敏感限制的节点免疫

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摘要

When we encounter a malicious rumor or an infectious disease outbreak, immunizing k nodes of the relevant network with limited resources is always treated as an extremely effective method. The key challenge is how we can insulate limited nodes to minimize the propagation of those contagious things. In previous works, the best k immunised nodes are selected by learning the initial status of nodes and their strategies even if there is no feedback in the propagation process, which eventually leads to ineffective performance of their solutions. In this paper, we design a novel vaccines placement strategy for protecting much more healthy nodes from being infected by infectious nodes. The main idea of our solution is that we are not only utilizing the status of changing nodes as auxiliary knowledge to adjust our scheme, but also comparing the performance of vaccines in various transmission slots. Thus, our solution has a better chance to get more benefit from these limited vaccines. Extensive experiments have been conducted on several real-world data sets and the results have shown that our algorithm has a better performance than previous works.
机译:当我们遇到恶意谣言或传染病暴发时,以有限的资源免疫相关网络的k个节点始终被视为一种非常有效的方法。关键的挑战是我们如何隔离有限的节点,以最大程度地减少那些具有传染性的事物的传播。在以前的工作中,即使传播过程中没有反馈,通过学习节点的初始状态及其策略来选择最佳的k个免疫节点,这最终会导致其解决方案的效果不佳。在本文中,我们设计了一种新颖的疫苗放置策略,以保护更多健康的节点免受感染性节点的感染。我们解决方案的主要思想是,我们不仅将变化节点的状态作为辅助知识来调整我们的方案,而且还将比较各种传输时隙中疫苗的性能。因此,我们的解决方案更有机会从这些有限的疫苗中获得更多收益。在几个真实的数据集上进行了广泛的实验,结果表明我们的算法比以前的工作有更好的性能。

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