An adaptive algorithm for efficient message diffusion in unreliable environments

B. Garbinato, F. Pedone, R. Schmidt
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引用次数: 24

Abstract

In this paper, we propose a novel approach for solving the reliable broadcast problem in a probabilistic unreliable model. Our approach consists in first defining the optimality of probabilistic reliable broadcast algorithms and the adaptiveness of algorithms that aim at converging toward such optimality. Then, we propose an algorithm that precisely converges toward the optimal behavior, thanks to an adaptive strategy based on Bayesian statistical inference. We compare the performance of our algorithm with that of a typical gossip algorithm through simulation. Our results show, for example, that our adaptive algorithm quickly converges toward such exact knowledge.
一种不可靠环境下有效消息扩散的自适应算法
本文提出了一种解决概率不可靠模型中可靠广播问题的新方法。我们的方法包括首先定义概率可靠广播算法的最优性和旨在向这种最优性收敛的算法的自适应。然后,我们提出了一种基于贝叶斯统计推断的自适应策略的算法,该算法精确地收敛于最优行为。通过仿真,将该算法的性能与典型的八卦算法进行了比较。例如,我们的结果表明,我们的自适应算法可以迅速收敛到这些精确的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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