How to assign votes in a distributed system
Journal of the ACM (JACM)
The vulnerability of vote assignments
ACM Transactions on Computer Systems (TOCS)
Optimal coteries and voting schemes
Information Processing Letters
Globally Optimal Diagnosis in Systems with Random Faults
IEEE Transactions on Computers
Optimal Diagnosis of Heterogeneous Systems with Random Faults
IEEE Transactions on Computers
Reaching Agreement in the Presence of Faults
Journal of the ACM (JACM)
Distributed Algorithms
IEEE Transactions on Computers
Voting as the Optimal Static Pessimistic Scheme for Managing Replicated Data
IEEE Transactions on Parallel and Distributed Systems
Fast fault-tolerant agreement algorithms
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
The weakest failure detector to solve nonuniform consensus
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
The truth system: can a system of lying processes stabilize?
SSS'07 Proceedings of the 9h international conference on Stabilization, safety, and security of distributed systems
Robust network supercomputing without centralized control
OPODIS'11 Proceedings of the 15th international conference on Principles of Distributed Systems
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A Boolean value of given a priori probability distribution is transmitted to a deciding agent by several processes. Each process fails independently with given probability, and faulty processes behave in a Byzantine way. A deciding agent has to make a decision concerning the transmitted value on the basis of messages obtained by processes. We construct a deterministic decision strategy which has the provably highest probability of correctness. It computes the decision in time linear in the number of processes. Decision optimality may be alternatively approached from a local, rather than global, point of view. Instead of maximizing the total probability of correctness of a decision strategy, we may try to find, for every set of values conveyed by processes, the conditionally most probable original value that could yield this set. We call such a strategy locally optimal, as it locally optimizes the probability of a decision, given a set of relayed values, disregarding the impact of such a choice on the overall probability of correctness. We construct a locally optimal decision strategy which again computes the decision value in time linear in the number of processes. We establish the surprising fact that, in general, local probability maximization may lead to a decision strategy which does not have the highest probability of correctness. However, if the probability distribution of the Boolean value to be conveyed is uniform, and all processes have the same failure probability smaller than 12, this anomaly does not occur. We first design and analyze our strategies in the synchronous setting and then show how they should be modified to work in asynchronous systems.