Brief Announcement: A Family of Leaderless Generalized-Consensus Algorithms

Leaderless consensus algorithms in the vein of EPaxos have performance advantages, especially for geo-replication, but are also very intricate, making them hard to modify and adapt for specific use cases. In this paper we show that their core principle can be captured in a generic leaderless generalized-consensus algorithm that uses two new abstractions: a dependency-set algorithm, which suggests dependencies for commands, and a map-agreement algorithm, which ensures that, for each submitted command, processes agree on a dependency set. Our generic algorithm gives rise to a family of algorithms whose members are obtained by using concrete dependency-set and map-agreement algorithms. On top of enabling modular correctness proofs of leaderless consensus algorithms, we expect that the modular structure of our generic leaderless algorithm will allow a principled theoretical and empirical evaluation of the trade-offs that can be achieved by different implementations of our two abstractions.