Simultaneous consensus tasks: A tighter characterization of set-consensus

Yehuda Afek, Eli Gafni, Sergio Rajsbaum, Michel Raynal, Corentin Travers

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We address the problem of solving a task T = (T1, ⋯T m) (called (m, 1)-BG), in which a processor returns in an arbitrary one of m simultaneous consensus subtasks T1, ⋯Tm. Processor pi submits to T an input vector of proposals (prop i,1, ⋯, propi, m), one entry per subtask, and outputs, from just one subtask ℓ, a pair (ℓ, propj, l) for some j. All processors that output at ℓ output the same proposal. Let d be a bound on the number of distinct input vectors that may be submitted to T. For example, d = 3 if Democrats always vote Democrats across the board, and similarly for Republicans and Libertarians. A wait-free algorithm that immaterial of the number of processors solves T provided m ≥ d is presented. In addition, if in each Tj we allow k-set consensus rather than consensus, i.e., for each ℓ, the outputs satisfy |{j|prop j,ℓ}| ≤ k, then the same algorithm solves T if m ≥ ⌊d/k⌋. What is the power of T = (T1,⋯, T m) when given as a subroutine, to be used by any number of processors with any number of input vectors? Obviously, T solves m-set consensus since each processor pi can submit the vector (idi, id i, ⋯idi), but can m-set consensus solve T? We show it does, and thus simultaneous consensus is a new characterization of set-consensus. Finally, what if each Tj is just a binary-consensus rather than consensus? Then we get the novel problem that was recently introduced of the Committee-Decision. It was shown that for 3 processors and m = 2, the simultaneous binary-consensus is equivalent to (3, 2)-set consensus. Here, using a variation of our wait-free algorithms mentioned above, we show that a task, in which a processor is required to return in one of m simultaneous binary-consensus sub-tasks, when used by n processors, is equivalent to (n, m)-set consensus. Thus, while set-consensus unlike consensus, has no binary version, now that we characterize m-set consensus through simultaneous consensus, the notion of binary-set-consensus is well defined. We have then showed that binary-set-consensus is equivalent to set consensus as it was with consensus.

Original languageEnglish
Title of host publicationDistributed Computing and Networking - 8th International Conference, ICDCN 2006, Proceedings
Pages331-341
Number of pages11
DOIs
StatePublished - 2006
Event8th International Conference on Distributed Computing and Networking, ICDCN 2006 - Guwahati, India
Duration: 27 Dec 200630 Dec 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4308 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Distributed Computing and Networking, ICDCN 2006
Country/TerritoryIndia
CityGuwahati
Period27/12/0630/12/06

Fingerprint

Dive into the research topics of 'Simultaneous consensus tasks: A tighter characterization of set-consensus'. Together they form a unique fingerprint.

Cite this