An optimized conflict-free replicated set

TL;DR

This paper introduces an optimized conflict-free replicated set that enhances eventual consistency by reducing meta-data size, using permutation equivalence to analyze concurrency semantics and proposing an efficient optimization to avoid tombstones.

Contribution

It presents a new optimization for conflict-free replicated sets that reduces meta-data size and introduces permutation equivalence as a framework for concurrency semantics.

Findings

Reduced meta-data size by avoiding tombstones.

Applied permutation equivalence to characterize concurrency semantics.

Optimized approach applicable to other data types like maps and graphs.

Abstract

Eventual consistency of replicated data supports concurrent updates, reduces latency and improves fault tolerance, but forgoes strong consistency. Accordingly, several cloud computing platforms implement eventually-consistent data types. The set is a widespread and useful abstraction, and many replicated set designs have been proposed. We present a reasoning abstraction, permutation equivalence, that systematizes the characterization of the expected concurrency semantics of concurrent types. Under this framework we present one of the existing conflict-free replicated data types, Observed-Remove Set. Furthermore, in order to decrease the size of meta-data, we propose a new optimization to avoid tombstones. This approach that can be transposed to other data types, such as maps, graphs or sequences.