• Publications
  • Influence
Self-stabilizing extensions for message-passing systems
A self-stabilizing program eventually resumes normal behavior even if excution begins in, an abnormal initial state. Expand
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Distributed agreement in the presence of processor and communication faults
A model of distributed computation is proposed in which processes may fail by not sending or receiving the message specified by a protocol. Expand
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Towards optimal distributed consensus
In a distributed consensus protocol all processors (of which t may be faulty) are given (binary) initial values; after exchanging messages all correct processors must agree on one of them. Expand
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  • PDF
Fast Distributed Agreement
We describe a Byzantine Agreement algorithm, with early stopping, for systems with arbitrary process failures, that restricts the disruptive behavior of faulty processes. Expand
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Self-stabilizing extensions for meassage-passing systems
A formal definition of the concept of one program being a self-stabilizing extension of another; (2) a characterization of what properties may hold in such extensions; (3) a demonstration of the possibility of mechanically creating such extensions. Expand
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Bit optimal distributed consensus
The Distributed Consensus problem involves n processors each of which holds an initial binary value. Expand
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A Continuum of Failure Models for Distributed Computing
A range of models of distributed computing is presented in which processors may fail either by crashing or by exhibiting arbitrary (Byzantine) behavior. Expand
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Randomized Byzantine Agreement
  • K. Perry
  • Art, Computer Science
  • IEEE Transactions on Software Engineering
  • 1 June 1985
A randomized model of distributed computation was recently presented by Rabin [ 81. Expand
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Towards Optimal Distributed Consensus (Extended Abstract)
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Optimal Early Stopping in Distributed Consensus (Extended Abstract)
This paper presents consensus protocols that tolerate arbitrary faults, are early-stopping (i.e., run for a number of rounds proportional to the number of faults f that actually occur during their execution), and are optimal in various measures. Expand
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