Fast perfect-information leader-election protocol with linear immunity

Jason Cooper, Nathan Linial

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

9 Scopus citations


In this paper we develop a leader election protocol P with the following features: The protocol runs in the perfect information model: Every step taken by a player is visible to all others. It has linear immunity: If P is run by n players and a coalition of c1n players deviates from the protocol, attempting to have one of them elected, their probability of success is < 1 -C2, where Ci, c2 > 0 are absolute constants. It is fast : The running time of P is poly- logarithmic in n, the number of players. A previous protocol by Alon and Naor achieving linear immunity in the perfect information model has a linear time complexity. The main ingredient of our protocol is a reduction subpro-Tocol. This is a way for n players to elect a subset of themselves which has the following property. Assume that up to €n of the players are bad and try to have as many of them elected to the subset. Then with high probability, the fraction of bad players among the elected ones will not exceed € in a significant way. The existence of such a reduction protocol is first established by a probabilistic argument. Later an explicit construction is provided which is based on the spectral properties of Ramanujan graphs.

Original languageAmerican English
Title of host publicationProceedings of the 25th Annual ACM Symposium on Theory of Computing, STOC 1993
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)0897915917
StatePublished - 1 Jun 1993
Event25th Annual ACM Symposium on Theory of Computing, STOC 1993 - San Diego, United States
Duration: 16 May 199318 May 1993

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
VolumePart F129585
ISSN (Print)0737-8017


Conference25th Annual ACM Symposium on Theory of Computing, STOC 1993
Country/TerritoryUnited States
CitySan Diego

Bibliographical note

Publisher Copyright:
© 1993 ACM.


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