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Modular randomized byzantine k-set agreement in asynchronous message-passing systems

Published:04 January 2016Publication History

ABSTRACT

k-Set agreement is a central problem of fault-tolerant distributed computing. Considering a set of n processes, where up to t may commit failures, let us assume that each process proposes a value. The problem consists in defining an algorithm such that each non-faulty process decides a value, at most k different values are decided, and the decided values satisfy some context-depending validity condition. Synchronous message-passing algorithms solving k-set agreement have been proposed for different failure models (mainly process crashes, and process Byzantine failures). Differently, k-set agreement cannot be solved in failure-prone asynchronous message-passing systems when tk. To circumvent this impossibility an asynchronous system must be enriched with additional computational power.

Assuming tk, this paper presents a distributed algorithm that solves k-set agreement in an asynchronous message-passing system where up to t processes may commit Byzantine failures. To that end, each process is enriched with randomization power. While randomized k-set agreement algorithms exist for the asynchronous process crash failure model where tk, to our knowledge the proposed algorithm is the first that solves k-set agreement in the presence of up to tk Byzantine processes. Interestingly, this algorithm is signature-free, and ensures that no value proposed only by Byzantine processes can be decided by a non-faulty process. Its design is based on a modular construction which rests on a "no-duplicity" one-to-all broadcast abstraction, and two all-to-all communication abstractions.

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          cover image ACM Other conferences
          ICDCN '16: Proceedings of the 17th International Conference on Distributed Computing and Networking
          January 2016
          370 pages
          ISBN:9781450340328
          DOI:10.1145/2833312

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          Publication History

          • Published: 4 January 2016

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