Coordination-free Collaborative Replication based on Operational Transformation

TL;DR

This paper presents CCR, a novel coordination-free method for maintaining consistency in distributed systems that combines operational transformation principles with conflict resolution, improving efficiency and usability over existing CRDT approaches.

Contribution

It introduces CCR, a new decentralized replication method that automates conflict resolution without coordination, integrating OT concepts with data stream confluence for better performance.

Findings

CCR enables conflict-free, coordination-free replication in distributed systems.

CCR improves efficiency over traditional CRDTs by reducing messaging overhead.

CCR offers more intuitive conflict resolution compared to existing methods.

Abstract

We introduce Coordination-free Collaborative Replication (CCR), a new method for maintaining consistency across replicas in distributed systems without requiring explicit coordination messages. CCR automates conflict resolution, contrasting with traditional Data-sharing systems that typically involve centralized update management or predefined consistency rules. Operational Transformation (OT), commonly used in collaborative editing, ensures consistency by transforming operations while maintaining document integrity across replicas. However, OT assumes server-based coordination, which is unsuitable for modern, decentralized Peer-to-Peer (P2P) systems. Conflict-free Replicated Data Type (CRDT), like Two-Phase Sets (2P-Sets), guarantees eventual consistency by allowing commutative and associative operations but often result in counterintuitive behaviors, such as failing to re-add an item to a shopping cart once removed. In contrast, CCR employs a more intuitive approach to replication. It allows for straightforward updates and conflict resolution based on the current data state, enhancing clarity and usability compared to CRDTs. Furthermore, CCR addresses inefficiencies in messaging by developing a versatile protocol based on data stream confluence, thus providing a more efficient and practical solution for collaborative data sharing in distributed systems.