Impossibility of distributed consensus with one faulty process
Journal of the ACM (JACM)
Unreliable failure detectors for reliable distributed systems
Journal of the ACM (JACM)
Structured derivations of consensus algorithms for failure detectors
PODC '98 Proceedings of the seventeenth annual ACM symposium on Principles of distributed computing
Self-stabilizing systems in spite of distributed control
Communications of the ACM
A mutual exclusion algorithm for ad hoc mobile networks
Wireless Networks
Early Detection of Message Forwarding Faults
SIAM Journal on Computing
Cross-Over Composition - Enforcement of Fairness under Unfair Adversary
WSS '01 Proceedings of the 5th International Workshop on Self-Stabilizing Systems
Dijkstra's Self-Stabilizing Algorithm in Unsupportive Environments
WSS '01 Proceedings of the 5th International Workshop on Self-Stabilizing Systems
Appraising two decades of distributed computing theory research
Distributed Computing - Papers in celebration of the 20th anniversary of PODC
Optimal decision strategies in Byzantine environments
Journal of Parallel and Distributed Computing
Self-stabilizing Byzantine digital clock synchronization
SSS'06 Proceedings of the 8th international conference on Stabilization, safety, and security of distributed systems
A Byzantine-fault tolerant self-stabilizing protocol for distributed clock synchronization systems
SSS'06 Proceedings of the 8th international conference on Stabilization, safety, and security of distributed systems
On the power of anonymous one-way communication
OPODIS'05 Proceedings of the 9th international conference on Principles of Distributed Systems
An Algorithm Evaluating System Stability to Process
ICA3PP '09 Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing
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We introduce a new abstract system, called the truth system. In the truth system, a process deduces a true value, with high probability, from an incoming stream of both true and false values, where the probability that a value in the incoming stream is true is at least 0.6. At each instant, the receiving process maintains at most one candidate of the true value, and eventually the process reaches the conclusion that its candidate value equals, with high probability, the true value. In this paper, we present three versions of the truth system, discuss their properties, and show how to choose their parameters so that their probability of error is small, i.e. about 10-6. The third version, called the stable system, is the most valuable. We employ the stable system as a building block in a stabilizing unidirectional token ring of n processes. When n is small, i.e. about 100 or less, the stable system can be considered errorfree and we argue that the resulting token ring is stabilizing with high probability. We simulate the token ring, when n is at most 100, and observe that the ring always stabilizes even though each process lies about its state 40% of the time.