Chandra–Toueg consensus algorithm

The Chandra–Toueg consensus algorithm, published by Tushar Deepak Chandra and Sam Toueg in 1996, is an algorithm for solving consensus in a network of unreliable processes equipped with an eventually strong failure detector. The failure detector is an abstract version of timeouts; it signals to each process when other processes may have crashed. An eventually strong failure detector is one that never identifies some specific non-faulty process as having failed after some initial period of confusion, and, at the same time, eventually identifies all faulty processes as failed (where a faulty process is a process which eventually fails or crashes and a non-faulty process never fails). The Chandra–Toueg consensus algorithm assumes that the number of faulty processes, denoted by f, is less than

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enThe Chandra–Toueg consensus algorithm, published by Tushar Deepak Chandra and Sam Toueg in 1996, is an algorithm for solving consensus in a network of unreliable processes equipped with an eventually strong failure detector. The failure detector is an abstract version of timeouts; it signals to each process when other processes may have crashed. An eventually strong failure detector is one that never identifies some specific non-faulty process as having failed after some initial period of confusion, and, at the same time, eventually identifies all faulty processes as failed (where a faulty process is a process which eventually fails or crashes and a non-faulty process never fails). The Chandra–Toueg consensus algorithm assumes that the number of faulty processes, denoted by f, is less than
Has abstract
enThe Chandra–Toueg consensus algorithm, published by Tushar Deepak Chandra and Sam Toueg in 1996, is an algorithm for solving consensus in a network of unreliable processes equipped with an eventually strong failure detector. The failure detector is an abstract version of timeouts; it signals to each process when other processes may have crashed. An eventually strong failure detector is one that never identifies some specific non-faulty process as having failed after some initial period of confusion, and, at the same time, eventually identifies all faulty processes as failed (where a faulty process is a process which eventually fails or crashes and a non-faulty process never fails). The Chandra–Toueg consensus algorithm assumes that the number of faulty processes, denoted by f, is less than n/2 (i.e. the minority), i.e. it assumes f < n/2, where n is the total number of processes.
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Algorithm
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Chandra–Toueg consensus algorithm
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enChandra–Toueg consensus algorithm
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portal.acm.org/citation.cfm%3Fcoll=GUIDE&dl=GUIDE&id=226647
www.cs.yale.edu/homes/aspnes/pinewiki/FailureDetectors.html
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Category:Distributed algorithms
Category:Fault-tolerant computer systems
Consensus (computer science)
Failure detector
Timeout (computing)
Timestamp
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4hNPy
m.0b778 n
Q5071480
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Category:Distributed algorithms
Category:Fault-tolerant computer systems
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Chandra–Toueg consensus algorithm?oldid=1093255983&ns=0
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