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Novel method for spreading information with fewer resources in scale-free networks

机译:在无规模网络中使用较少资源传播信息的新方法

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Optimised spreading strategy or spreading paths are extensively studied for improving the spreading efficiency. Moreover, the reduction of consumed resources of spreading information is also an optimized approach. In this paper, we propose a novel method for spreading information with fewer resources. The essential idea behind the proposed method is to request at most 80% participants to spread the information instead of requesting all participants in scale-free networks. To examine the validity of the proposed method, 60 groups of Monte Carlo experiments in nine synthetic and a real scale-free networks are designed. Experimental results demonstrated that (1) at most 80% vertices requested to spread information are adequate to achieve the nearly equivalent spreading efficiency of requesting all vertices in scale-free networks and (2) the specific number of requested spreaders are affected by the network topology. Our proposed method can be employed in emergency exercises for reducing the complexity of exercises and the consumed resources. (C) 2019 Elsevier B.V. All rights reserved.
机译:广泛研究优化的扩散策略或扩散路径,以提高扩展效率。此外,扩散信息的消耗资源的降低也是一种优化的方法。在本文中,我们提出了一种利用较少资源传播信息的新方法。所提出的方法背后的基本因因是要求大多数80%的参与者来传播信息,而不是请求在无规模网络中的所有参与者。为了检查所提出的方法的有效性,设计了60组蒙特卡罗实验,其中九个合成物和无规模无规程网络。实验结果表明,(1)最多80%的顶点要求传播信息是足够的,以实现在无规模网络中请求所有顶点的几乎等同的传播效率,并且(2)特定的请求扩展器的受访者受到网络拓扑的影响。我们所提出的方法可以在紧急练习中用于降低练习和消费资源的复杂性。 (c)2019 Elsevier B.v.保留所有权利。

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