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Rumor Spreading in Random Evolving Graphs

机译:谣言在随机演化图中传播

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In this paper, we aim at analyzing the classical information spreading Push protocol in dynamic networks. We consider the edge- Markovian evolving graph model which captures natural temporal dependencies between the structure of the network at time t, and the one at time t + 1. Precisely, a non-edge appears with probability p, while an existing edge dies with probability q. In order to fit with real-world traces, we mostly concentrate our study on the case where p = Ω(1/n) and q is constant. We prove that, in this realistic scenario, the Push protocol does perform well, completing information spreading in O(log n) time steps, w.h.p., even when the network is, w.h.p., disconnected at every time step (e.g., when p log n/n). The bound is tight. We also address other ranges of parameters p and q (e.g., p+q = 1 with arbitrary p and q, and p = Θ(1/n) with arbitrary q). Although they do not precisely fit with the measures performed on real-world traces, they can be of independent interest for other settings. The results in these cases confirm the positive impact of dynamism.
机译:在本文中,我们的目标是分析经典信息扩展在动态网络推送协议。我们认为其在时间t捕获网络的结构之间的自然时间相关的边沿马尔可夫不断发展图模型,和一个在时间t + 1,准确地说,非边缘出现的概率为p,而现有的边缘与模具概率为q。为了适应现实世界的痕迹,我们主要集中在的情况下,其中p =Ω(1 / N),我们的研究和q是恒定的。我们证明了,在这种现实情况下,按协议并表现良好,完成信息的O(log n)的时间步骤,传播WHP,即使在网络,WHP,在每个时间步长断开连接(例如,当p 日志N / N)。界限紧张。我们也解决(具有任意q例如,P + Q = 1任意p和q,和p =Θ(1 / n))的参数p和q的其他范围。虽然他们不正是对现实世界的痕迹执行措施合适,他们可以为其他设置独立的利益的。在这些情况下的结果证实活力的积极影响。

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