Randomized Multivalued Consensus

The Consensus problem is a fundamental problem one has to solve to implement reliable services or applications on top of asynchronous distributed systems prone to failures. Unfortunately , this problem cannot be solved in those systems as soon as one process can crash (Fischer-Lynch-Paterson's impossibility result). Two approaches have been investigated to circumvent this impossibility result. Both consist in enriching the underlying system with appropriate \oracles". The Unreliable Failure Detector concept proposed by Chandra and Toueg constitutes one family of such oracles. Since it has been proposed, the failure detector-based approach has given rise to several failure detector-based consensus protocols. The other family of oracles consists in allowing each process to use a random number generator. In that case, the protocol termination is only probabilistic. A few randomized consensus protocols for message-passing asynchronous distributed systems have been proposed. Moreover, they consider that processes can only propose values from a binary set. This paper proposes a new randomized consensus protocol that allows processes to propose arbitrary values. Contrarily to other randomized consensus protocols, the proposed protocol does not require the a priori knowledge of the set of values that can be proposed by processes. It relies on a relatively simple combination of randomization and reliable broadcast.