Tolerating failures of continuous-valued sensors
ACM Transactions on Computer Systems (TOCS)
ACM Computing Surveys (CSUR)
Optimal amortized distributed consensus
Information and Computation
Self-stabilization
Revisiting the PAXOS algorithm
Theoretical Computer Science
Distributed Algorithms
The Consensus Problem in Unreliable Distributed Systems (A Brief Survey)
Proceedings of the 1983 International FCT-Conference on Fundamentals of Computation Theory
Stability of long-lived consensus
Journal of Computer and System Sciences
Distributed Computing: Fundamentals, Simulations and Advanced Topics
Distributed Computing: Fundamentals, Simulations and Advanced Topics
Continuous consensus via common knowledge
TARK '05 Proceedings of the 10th conference on Theoretical aspects of rationality and knowledge
Self-stabilizing byzantine agreement
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Stability of Multivalued Continuous Consensus
SIAM Journal on Computing
The committee decision problem
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
On self-stabilizing synchronous actions despite byzantine attacks
DISC'07 Proceedings of the 21st international conference on Distributed Computing
Self-stabilizing Numerical Iterative Computation
SSS '08 Proceedings of the 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems
Average long-lived binary consensus: Quantifying the stabilizing role played by memory
Theoretical Computer Science
The optimal strategy for the average long-lived consensus
CSR'11 Proceedings of the 6th international conference on Computer science: theory and applications
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Consider a distributed system S of sensors, where the goal is to continuously output an agreed reading. The input readings of non-faulty sensors may change over time; and some of the sensors may be faulty (Byzantine). Thus, the system is required to repeatedly perform consensus on the input values. This paper investigates the following question: assuming the input values of all the non-faulty sensors remain unchanged for a long period of time, what can be said about the agreed-upon output reading of the entire system? We prove that no system's output is stable, i.e. the faulty sensors can force a change of the output value at least once. We show that any system with binary input values can avoid changing its output more than once, thus matching the lower bound. For systems with multi-value inputs, we show that the output may change at most twice; when n=3f+1 this solution is shown to be tight. Moreover, the solutions we present are self-stabilizing.