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The correctness proof of Ben-Or's randomized consensus algorithm

机译:Ben-Or随机共识算法的正确性证明

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摘要

In a ground-breaking paper that appeared in 1983, Ben-Or presented the first randomized algorithm to solve consensus in an asynchronous message-passing system where processes can fail by crashing. Although more efficient randomized algorithms were subsequently proposed, Ben-Or's algorithm is still the simplest and most elegant one. For this reason, it is often taught in distributed computing courses and it appears in several textbooks. Even though Ben-Or's algorithm is widely known and it is very simple, surprisingly a proof of correctness of the algorithm has not yet appeared: previously published proofs make some simplifying assumptions-specifically, they either assume that / < n/3 (n is the total number of processes and / is maximum number of processes that may crash) or that the adversary is weak, that is, it cannot see the process states or the content of the messages. In this paper, we present a correctness proof for Ben-Or's randomized consensus algorithm for the case that / < n/2 process crashes and the adversary is strong (i.e., it can see the process states and message contents, and schedule the process steps and message receipts accordingly). To the best of our knowledge, this is the first full proof of this classical algorithm. We also demonstrate a counterintuitive problem that may occur if one uses the well-known abstraction of a "global coin" to modularize and speed up randomized consensus algorithms, such as Ben-Or's algorithm. Specifically, we show that contrary to common belief, the use of a global coin can sometimes be deleterious rather than beneficial: instead of speeding up Ben-Or's algorithm, the use of a global coin in this algorithm may actually prevent termination.
机译:在1983年发表的一篇开创性论文中,Ben-Or提出了第一个随机算法来解决异步消息传递系统中的共识,在异步消息传递系统中,进程可能因崩溃而失败。尽管随后提出了更有效的随机算法,但Ben-Or算法仍然是最简单,最优雅的算法。因此,它经常在分布式计算课程中教授,并出现在几本教科书中。尽管Ben-Or算法广为人知且非常简单,但令人惊讶的是尚未出现该算法正确性的证明:先前发表的证明做出了一些简化的假设-具体来说,它们要么假设/

著录项

  • 来源
    《Distributed Computing》 |2012年第5期|p.371-381|共11页
  • 作者

    Marcos K. Aguilera; Sam Toueg;

  • 作者单位

    Microsoft Research Silicon Valley, 1065 La Avenida, Mountain View, CA 94043, USA;

    University of Toronto, 10 King's College Road, Toronto, ON M5S 3G4, Canada;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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