PRDTs: Composable Knowledge-Based Consensus Protocols with Replicated Data Types

2025-04-07

AI Summary

Designing customized consensus protocols for distributed systems is labor-intensive, error-prone, and difficult to verify; existing Paxos/Raft variants require full reimplementation, hindering scenario-specific adaptability. This paper introduces Protocol Replicated Data Types (PRDTs), the first framework unifying consensus logic by grounding it in monotonic knowledge growth—integrating monotonic replicated data types (RDTs) with epistemic consensus semantics. We propose RDT algebraic composition, enabling modular, composable protocol construction. We formally prove that correctness properties—including safety and liveness—are derivable from PRDT specifications. Empirically, PRDTs faithfully reconstruct canonical protocols (e.g., Paxos, Raft) with performance on par with hand-optimized implementations. PRDTs substantially lower the barrier to custom protocol design while ensuring formal verifiability, flexibility, maintainability, and industrial deployability.

Technology Category

• Knowledge Representation and Reasoning: Nonmonotonic Reasoning
• Multiagent Systems: Mechanism Design
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust

Application Category

• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

Consensus protocols are fundamental in distributed systems as they enable software with strong consistency properties. However, designing optimized protocols for specific use-cases under certain system assumptions is typically a laborious and error-prone process requiring expert knowledge. While most recent optimized protocols are variations of well-known algorithms like Paxos or Raft, they often necessitate complete re-implementations, potentially introducing new bugs and complicating the application of existing verification results.This approach stands in the way of application-specific consistency protocols that can easily be amended or swapped out, depending on the given application and deployment scenario. We propose Protocol Replicated Data Types (PRDTs), a novel programming model for implementing consensus protocols using replicated data types (RDTs). Inspired by the knowledge-based view of consensus, PRDTs employ RDTs to monotonically accumulate until agreement is reached. This approach allows for implementations focusing on high-level protocol logic with minimal network environment assumptions. Moreover, by applying existing algebraic composition techniques for RDTs in the PRDT context, we enable composable protocol building-blocks for implementing complex protocols. We present a formal model of our approach, demonstrate its application in PRDT-based implementations of existing protocols, and report empirical evaluation results. Our findings indicate that the PRDT approach offers enhanced flexibility and composability in protocol design, facilitates reasoning about correctness, and does not suffer from inherent performance limitations that would prevent its use in real-world applications.

Problem

• Designing optimized consensus protocols is laborious and error-prone
• Existing protocols require re-implementation, risking bugs and complexity
• Application-specific consistency protocols lack flexibility and composability

Innovation

• PRDTs use replicated data types for consensus
• Composable protocol blocks via algebraic RDT techniques
• Minimal network assumptions with high-level logic focus