Randomization and Failure Detection: A Hybrid Approach to Solve Consensus (1996)
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| Venue: | In Proceedings of the 10th International Workshop on Distributed Algorithms, Lecture Notes on Computer Science |
| Citations: | 7 - 2 self |
BibTeX
@INPROCEEDINGS{Aguilera96randomizationand,
author = {Marcos K. Aguilera and Sam Toueg},
title = {Randomization and Failure Detection: A Hybrid Approach to Solve Consensus},
booktitle = {In Proceedings of the 10th International Workshop on Distributed Algorithms, Lecture Notes on Computer Science},
year = {1996},
pages = {29--39},
publisher = {Springer-Verlag}
}
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Abstract
We present a Consensus algorithm that combines randomization and unreliable failure detection, two well-known techniques for solving Consensus in asynchronous systems with crash failures. This hybrid algorithm combines advantages from both approaches: it guarantees deterministic termination if the failure detector is accurate, and probabilistic termination otherwise. In executions with no failures or failure detector mistakes, the most likely ones in practice, Consensus is reached in only two asynchronous rounds. 1 Background It is well-known that Consensus cannot be solved in asynchronous systems with failures, even if communication is reliable, at most one process may fail, and it can only fail by crashing. This "impossibility of Consensus", shown in a seminal paper by Fischer, Lynch and Paterson [FLP85], has been the subject of intense research seeking to "circumvent" this negative result (e.g., [Ben83, BT83, Rab83, DDS87, DLS88, CT96, CHT96]). We focus on two of the major ...
