STORChain: A Clustered-MPT-Based Blockchain for Data Service and Efficient Storage in Healthcare

Abstract

The adoption of blockchain technology in healthcare has significantly enhanced data integrity, transparency, and user privacy. However, high storage overhead and resource-intensive operations remain major challenges to its widespread deployment, particularly in large-scale or resource-constrained healthcare environments. To address these challenges, we propose STORChain, a storage-optimized blockchain framework designed for data services in healthcare. The framework introduces the Clustered Merkle Patricia Tree (C-MPT), a novel logical structure that aggregates similar transaction types to maximize storage efficiency while ensuring Proof of Inclusion (PoI). A Selective Transaction Pruning Strategy (STPS) is employed to prioritize and prune essential historical data, improving data access efficiency. Additionally, an incentive-based Delegated Proof-of-Stake (DPoS) consensus algorithm is utilized, integrating a probabilistic election mechanism to promote fairness and node inclusivity. Comprehensive theoretical analysis and practical experiment results indicate that STORChain significantly reduces storage overhead, optimizes data access, and outperforms existing schemes.