可伸缩的自动稳定

Sukumar Ghosh, Xin He
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引用次数: 21

摘要

本文提出了一种异步无功分布式系统在与系统规模无关的、以k为单调递增函数的时间内从k故障状态稳定下来的方法。在提出的方法中,过程首先测量故障区域的大小,然后使用该信息来调度操作,从而使故障区域逐渐缩小,直到它们完全消失。当k个连续进程失败时,稳定时间为O(k/sup 3/)。否则,对于较小的k值,稳定时间可以以k为指数,但其上界为0 (n/sup 3/)。每个进程增加的空间复杂度为0 (/spl delta/ log/sub 2/n),其中/spl delta/表示节点的最大程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scalable self-stabilization
The paper presents a method by which an asynchronous non-reactive distributed system can stabilize from a k-faulty configuration in a time that is a monotonically increasing function of k and independent of the size of the system. In the proposed methodology processes first measure the size of the faulty regions, and then use this information to schedule actions in such a way that the faulty regions progressively shrink, until they completely disappear. When k contiguous processes fail, the stabilization time is O(k/sup 3/). Otherwise, for small values of k, the stabilization time can be exponential in k, but it has an upper bound of O(n/sup 3/). The added space complexity per process is O(/spl delta/ log/sub 2/n), where /spl delta/ is the maximum degree of a node.
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