First passage percolation in sparse random graphs with boundary weights

Research output: Contribution to journalArticleScientificpeer-review


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.
Original languageEnglish
Pages (from-to)458-471
Number of pages14
JournalJournal of Applied Probability
Issue number2
Publication statusPublished - 30 Jul 2019
MoE publication typeA1 Journal article-refereed

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