一种新的无一致假设的源定位策略

Xinyan She, Xianghua Li, Yuxin Liu, Chao Gao
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引用次数: 4

摘要

在复杂网络领域中,定位传播源是一个普遍存在但具有挑战性的问题。传统的基于一组观测器的信号源定位方法可以达到较高的定位精度。然而,如此高的精度是建立在一致性假设的基础上的,即传播延迟在感染时间计算过程和源定位过程中都始终遵循一定的分布。根据我们的仿真结果和已有的研究,我们发现在一些现实场景中,真实的传播延迟往往会打破这种一致性假设,在这种情况下,现有方法的预测精度会显著下降。因此,它提出了一个关键问题:我们能否在不假设传播延迟分布的情况下定位感染源?本文首先将源定位问题表述为基于一组观测器的传播时延参数的推断问题。然后,我们提出了一种新的反向传播策略来定位传染源。最后,通过综合比较,对我们的方法进行了定量分析。结果表明,该策略比没有一致性假设的传统方法具有更高的准确率。
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A novel source locating strategy without consistent assumptions
Locating the source of propagation is a ubiquitous but challenging problem in the field of complex networks. The traditional source location methods based on a set of observers can achieve a high locating accuracy. However, such high accuracy is based on the consistent assumption which means the propagation delays consistently follow a certain distribution in both the infected time calculation process and the source location process. Based on our simulation results and existing researches, we find that the real propagation delays, in some real-world scenarios, often break such consistent assumption and the predication accuracy of existing methods decline significantly in these circumstances. Therefore it raises a critical question: can we locate the infection source without assuming the distribution of propagation delays? In this paper, we first formulate the problem of locating source as inferring the parameters of propagation delays based on a set of observers. Then, we propose a novel reverse propagation strategy to locate infection source. Finally, a comprehensive comparisons are used to provide a quantitative analyses of our method. The results show that our strategy has a higher accuracy than the traditional methods without the consistent assumptions.
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