# Linearizable State Machine Replication of State-Based CRDTs without Logs

**Authors:** Jan Skrzypczak, Florian Schintke, Thorsten Sch\"utt

arXiv: 1905.08733 · 2020-07-27

## TL;DR

This paper introduces a novel protocol for linearizable state machine replication of CRDTs that eliminates the need for consensus or a leader, significantly reducing synchronization costs and improving throughput in distributed systems.

## Contribution

It presents a leaderless, consensus-free protocol for linearizable CRDT replication leveraging monotonic growth, enabling in-place updates and minimal message overhead.

## Key findings

- Over 99% of queries handled in 1-3 round trips
- Significant reduction in synchronization overhead compared to traditional methods
- High throughput achieved without leader election or command logs

## Abstract

General solutions of state machine replication have to ensure that all replicas apply the same commands in the same order, even in the presence of failures. Such strict ordering incurs high synchronization costs caused by distributed consensus or by the use of a leader.   This paper presents a protocol for linearizable state machine replication of conflict-free replicated data types (CRDTs) that neither requires consensus nor a leader. By leveraging the properties of state-based CRDTs - in particular, the monotonic growth of a join semilattice - synchronization overhead is greatly reduced. As a result, updates only need a single round trip and modify the state 'in-place' without the need for a log. Furthermore, the message size overhead for coordination consists of a single counter per message. For queries, we guarantee finite writes termination. We show in an experimental evaluation that more than 99 % of queries can be handled in one to three round trips under highly concurrent accesses.   Our protocol achieves high throughput without auxiliary processes such as command log management or leader election. Thus, it is well suited for practical scenarios that need linearizable access to CRDT data on a fine-granular scale.

## Full text

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## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/1905.08733/full.md

## References

46 references — full list in the complete paper: https://tomesphere.com/paper/1905.08733/full.md

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Source: https://tomesphere.com/paper/1905.08733