BlockRaFT: A Distributed Framework for Fault-Tolerant and Scalable Blockchain Nodes

2026-04-17

AI Summary

Existing blockchain nodes struggle to meet the demands of high throughput and high reliability due to limitations in scalability, availability, and fault tolerance. This work proposes a distributed node architecture based on the RAFT consensus protocol, which employs a leader-follower coordination mechanism to centralize stateless operations at the leader while replicating stateful operations across the cluster. By integrating a state partitioning strategy with concurrent Merkle tree update techniques, the design achieves load balancing and strong consistency. The proposed approach significantly enhances system scalability, fault tolerance, and overall performance, while effectively reducing the overhead associated with smart contract execution and Merkle tree maintenance.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Search and Optimization: Distributed Search
• Multiagent Systems: Mechanism Design

Application Category

• Security and Privacy: Blockchains and distributed ledgers
• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Economics, Online Markets and Human Computation: Economic aspects of blockchain and cryptocurrencies

Abstract

Blockchain technology enhances transparency by maintaining a distributed ledger among mutually untrusting parties. Despite its advantages, scalability and availability remain critical bottlenecks that hinder widespread adoption. The increasing complexity of blockchain nodes further necessitates robust fault tolerance and high throughput to ensure seamless operations. We present BlockRaFT, a crash-tolerant distributed framework designed to improve both the scalability and reliability of blockchain node operations. BlockRaFT framework utilizes RAFT consensus protocol to elect a leader within a cluster of systems. The elected leader coordinates and distributes workloads across follower nodes, thereby optimizing resource utilization and work load balancing. We analyzed the tasks performed by blockchain nodes and partition them according to their stateful and stateless characteristics. Stateless operations are centralized at the leader, while stateful operations are replicated and coordinated across the cluster to ensure consistency and fault tolerance. We evaluate whether this distributed intra-node architecture provides measurable benefits over traditional single-node execution models in terms of scalability, availability, and performance. Additionally, we introduce a concurrent Merkle tree optimization that decouples smart contract execution from tree updates, significantly reducing one of the significant performance overheads in blockchain systems. Our design philosophy is rooted in utilizing the well-established principles of distributed computing and customizing them for the blockchain domain rather than reinventing them.

Problem

• scalability
• availability
• fault tolerance
• blockchain nodes
• throughput

Innovation

• BlockRaFT
• Raft consensus
• stateful/stateless partitioning
• concurrent Merkle tree
• fault-tolerant blockchain