随机对称破缺分布式计算的拓扑结构

Pierre Fraigniaud, Ran Gelles, Zvi Lotker
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引用次数: 0

摘要

在过去的20年里,通过代数拓扑来研究分布式计算已经成为许多重大突破的来源,特别是在设计下界或不可能结果方面。尽管有数百个结果考虑确定性算法,但没有一个适用于随机算法。本文旨在从代数拓扑的角度研究随机同步分布式计算。我们通过研究同步无故障匿名系统中广泛的(无输入)对称破坏任务,例如领导者选举,来实现这一目标。我们设计了一个拓扑框架,它允许分析这些任务并确定它们的可解决性。关键的技术观察是,与确定性算法不同,确定性算法的可解性意味着描述协议的拓扑复合体可以全局映射到输出协议中,在我们的框架中,可解性是“局部”确定的,即,对于协议复合体的每个单纯形单独确定,而不需要任何全局一致性。作为一个有趣的应用,我们导出了解决共享内存和消息传递模型中领导者选举的充要条件,其中提供给节点的随机性之间可能存在相关性。我们发现领导人选举的可解性与具有相关随机性的政党数量有关,根据具体的通信模型,可以直接或通过其最大公约数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The topology of randomized symmetry-breaking distributed computing
Studying distributed computing through the lens of algebraic topology has been the source of many significant breakthroughs during the last 2 decades, especially in the design of lower bounds or impossibility results. Despite hundred of results considering deterministic algorithms, none apply to randomized algorithms. This paper aims at studying randomized synchronous distributed computing through the lens of algebraic topology. We do so by studying the wide class of (input-free) symmetry-breaking tasks, e.g., leader election, in synchronous fault-free anonymous systems. We design a topological framework, which allows analyzing such tasks and determining their solvability. The pivotal technical observation is that, unlike in deterministic algorithm, where solvability means that the topological complex describing the protocol can be globally mapped into an output protocol, in our framework the solvability is determined “locally”, i.e., for each simplex of the protocol complex individually, without requiring any global consistency. As an interesting application, we derive necessary and sufficient conditions for solving leader election in shared-memory and message-passing models in which there might be correlations between the randomness provided to the nodes. We find that solvability of leader election relates to the number of parties that possess correlated randomness, either directly or via their greatest common divisor, depending on the specific communication model.
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CiteScore
3.40
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