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Convergence time analysis of quantized gossip consensus on digraphs

机译:有向图量化八卦共识的收敛时间分析

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摘要

We have recently proposed quantized gossip algorithms which solve the consensus and averaging problems on directed graphs with the least restrictive connectivity requirements. In this paper we study the convergence time of these algorithms. To this end, we investigate the shrinking time of the smallest interval that contains all states for the consensus algorithm, and the decay time of a suitable Lyapunov function for the averaging algorithm. The investigation leads us to characterize the convergence time by the hitting time in certain special Markov chains. We simplify the structures of state transition by considering the special case of complete graphs, where every edge can be activated with an equal probability, and derive polynomial upper bounds on convergence time.
机译:我们最近提出了量化的八卦算法,该算法可以解决对连通性要求最低的有向图的共识和平均问题。在本文中,我们研究了这些算法的收敛时间。为此,我们研究了包含共识算法所有状态的最小间隔的收缩时间,以及用于平均算法的合适Lyapunov函数的衰减时间。调查使我们通过某些特殊的马尔可夫链中的命中时间来表征收敛时间。通过考虑完整图的特殊情况,我们简化了状态转换的结构,在这种情况下,每个边都可以以相等的概率激活,并得出收敛时间的多项式上限。

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