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arXiv 1806.09568math.PR
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带边界权的稀疏随机图的首次通过渗流

First passage percolation in sparse random graphs with boundary weights

Lasse Leskelä, Hoa Ngo

摘要:

具有独立指数分布链接权重的大型稀疏随机图可以用于对具有未知连接结构的网络中的消息或疾病的传播进行建模。在这篇文章中,我们研究了一个扩展的设置,其中图的节点也配备了非负随机权重,用于模拟网络中路径之间的边界延迟的影响。我们的主要结果提供了近似公式的典型的首次通过时间,典型的洪水时间,最大洪水时间在扩展设置,在一个时间尺度对数相对于网络的大小。

英文摘要:

A large and sparse random graph with independent exponentially distributed link weights can be used to model the propagation of messages or diseases in a network with an unknown connectivity structure. In this article we study an extended setting where also the nodes of the graph are equipped with nonnegative random weights which are used to model the effect of boundary delays across paths in the network. Our main results provide approximative formulas for typical first passage times, typical flooding times, and maximum flooding times in the extended setting, over a time scale logarithmic with respect to the network size.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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