首页> 外文会议>PODC'11 : Proceedings of the 2011 ACM symposium on principles of distributed computing. >Fast and Compact Self Stabilizing Verification, Computation, and Fault Detection of an MST
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Fast and Compact Self Stabilizing Verification, Computation, and Fault Detection of an MST

机译:MST的快速紧凑的自稳定验证,计算和故障检测

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This paper demonstrates the usefulness of distributed local verification of proofs, as a tool for the design of algorithms. In particular, it introduces a somewhat generalized notion of distributed local proofs, and utilizes it for improving the memory size complexity, while obtaining time efficiency too. As a result, we show that optimizing the memory size carries at most a small cost in terms of time, in the context of Minimum Spanning Tree (MST). That is, we present algorithms that are both time and space efficient for constructing an MST, for verifying it, and for detecting the location of the faults. This involves several steps that may be considered contributions in themselves. First, we generalize the notion of local proofs, trading off the locality (or, really, the time complexity) for memory efficiency. This adds a dimension to the study of distributed local proofs, that has been gaining attention recently. Second, as opposed to previous studies that presented only the labels verification part of a proof labeling schemes, we present here also a space and time efficient distributed self stabilizing marker algorithm to generates those labels. This presents proof labeling schemes as an algorithmic tool. Finally, we show how to enhance a known transformer that makes input/output algorithms self stabilizing. It now takes as input an efficient construction algorithm and an efficient self stabilizing proof labeling scheme, and produces an efficient self stabilizing algorithm. When used for MST, the transformer produces a memory optimal (i.e., O(log n) bits per node) self stabilizing algorithm, whose time complexity, namely, O(n), is significantly better even than that of previous algorithms that where not space optimal. (The time complexity of previous MST algorithms that used Ω(log~2 n) memory bits per node was O(n~2), and the time for optimal space algorithms was O(n|E|).) Our MST algorithm also has the important property that, if faults occur after the construction ended, then they are detected by some nodes within O(log~2 n) time in synchronous networks, or within O(Δ log~2 n) time in asynchronous ones. This property is inherited from the specific proof labeling scheme we construct. It answers an open problem posed by Awerbuch and Varghese (FOGS 1991). We also show that Ω(log n) time is necessary if the memory size is restricted to O(log n) bits, even in synchronous networks. Another property is that if f faults occurred, then, within the required detection time above, they are detected by some node in the O(f log n) locality of each of the faults. We also show how to improve the above detection time and locality, at the expense of some increase in the memory.
机译:本文演示了证明的分布式本地验证的有用性,作为设计算法的工具。特别是,它引入了分布式局部证明的某种概括性概念,并利用它来提高内存大小的复杂性,同时也获得了时间效率。结果,我们表明,在最小生成树(MST)的背景下,优化内存大小最多只花费少量时间。也就是说,我们提出的算法在构造MST,验证MST和检测故障位置方面都具有时间和空间效率。这涉及几个步骤,这些步骤本身可以被认为是贡献。首先,我们推广局部证明的概念,以牺牲局部性(或者实际上是时间复杂度)为代价来提高内存效率。这为分布式局部证明的研究增加了一个维度,该维度最近已引起关注。其次,与仅提供证明标签方案的标签验证部分的先前研究相反,我们在这里还提出了一种时空高效的分布式自稳定标记算法来生成这些标签。这将证明标签方案作为一种算法工具。最后,我们展示了如何增强一种已知的变压器,该变压器可以使输入/输出算法自稳定。现在,它将有效的构造算法和有效的自稳定证明标签方案作为输入,并产生有效的自稳定算法。当用于MST时,转换器会产生内存最佳(即每个节点O(log n)位)自稳定算法,其时间复杂度O(n)甚至比以前的算法要好得多,空间最佳。 (以前每个节点使用Ω(log〜2 n)个存储位的MST算法的时间复杂度为O(n〜2),最佳空间算法的时间为O(n | E |)。)我们的MST算法也具有重要的性质,如果故障在施工结束后发生,则在同步网络的O(log〜2 n)时间之内或在异步网络的O(Δlog〜2 n)时间之内,会被某些节点检测到。此属性继承自我们构建的特定证明标签方案。它回答了Awerbuch和Varghese提出的一个开放性问题(FOGS 1991)。我们还表明,即使将内存大小限制为O(log n)位,即使在同步网络中,Ω(log n)时间也是必需的。另一个特性是,如果发生了f个故障,则在上面要求的检测时间内,这些故障将被每个故障的O(f log n)局部中的某个节点检测到。我们还展示了如何改善上述检测时间和局部性,但要以牺牲一些内存为代价。

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