Chandra–Toueg consensus algorithm

Abstract: We introduce the concept of unreliable failure detectors and study how they can be used to solve Consensus in asynchronous systems with crash failures. We characterise unreliable failure detectors in terms of two properties—completeness and accuracy. We show that Consensus can be solved even with unreliable failure detectors that make an infinite number of mistakes, and determine which ones can be used to solve Consensus despite any number of crashes, and which ones require a majority of correct processes. We prove that Consensus and Atomic Broadcast are reducible to each other in asynchronous systems with crash failures; thus, the above results also apply to Atomic Broadcast. A companion paper shows that one of the failure detectors introduced here is the weakest failure detector for solving Consensus [Chandra et al. 1992].

Abstract: We determine what information about failures is necessary and sufficient to solve Consensus in asynchronous distributed systems subject to crash failures. In [CT91], we proved that $\Diamond\cal W$, a failure detector that provides surprisingly little information about which processes have crashed, is sufficient to solve Consensus in asynchronous systems with a majority of correct processes. In this paper, we prove that to solve Consensus, any failure detector has to provide at least as much information as $\Diamond\cal W$. Thus, $\Diamond\cal W$ is indeed the weakest failure detector for solving Consensus in asynchronous systems with a majority of correct processes.

Abstract: We determine what information about failures is necessary and sufficient to solve Consensus in asynchronous distributed systems subject to crash failures. In Chandra and Toueg [1996], it is shown that W, a failure detector that provides surprisingly little information about which processes have crashed, is sufficient to solve Consensus in asynchronous systems with a majority of correct processes. In this paper, we prove that to solve Consensus, any failure detector has to provide at least as much information as W. Thus, W is indeed the weakest failure detector for solving Consensus in asynchronous systems with a majority of correct processes.

Abstract: Reaching agreement is a primitive of distributed computing. Whereas this poses no problem in an ideal, failure-free environment, it imposes certain constraints on the capabilities of an actual system: A system is viable only if it permits the existence of consensus protocols tolerant to some number of failures. Fischer et al. have shown that in a completely asynchronous model, even one failure cannot be tolerated. In this paper their work is extended: Several critical system parameters, including various synchrony conditions, are identified and how varying these affects the number of faults that can be tolerated is examined. The proofs expose general heuristic principles that explain why consensus is possible in certain models but not possible in others.