Open Access

ARTICLE

LSBSP: A Lightweight Sharding Method of Blockchain Based on State Pruning for Efficient Data Sharing in IoMT

Guoqiong Liao^1,3, Yinxiang Lei^1,2,*, Yufang Xie¹, Neal N. Xiong⁴

1 College of Virtual Reality (VR) Modern Industry, Jiangxi University of Finance and Economics, Nanchang, 330032, China
2 School of Computer Science, Jiangxi University of Traditional Chinese Medicine, Nanchang, 330004, China
3 Jiangxi Tourism & Commerce Vocational College, Nanchang, 330100, China
4 Department of Computer, Mathematical and Physical Sciences, Sul Ross State University, Alpine, TX 79830, USA

* Corresponding Author: Yinxiang Lei. Email:

Computers, Materials & Continua 2025, 82(2), 3309-3335. https://doi.org/10.32604/cmc.2024.060077

Received 23 October 2024; Accepted 06 December 2024; Issue published 17 February 2025

Abstract

As the Internet of Medical Things (IoMT) continues to expand, smart health-monitoring devices generate vast amounts of valuable data while simultaneously raising critical security and privacy challenges. Blockchain technology presents a promising avenue to address these concerns due to its inherent decentralization and security features. However, scalability remains a persistent hurdle, particularly for IoMT applications that involve large-scale networks and resource-constrained devices. This paper introduces a novel lightweight sharding method tailored to the unique demands of IoMT data sharing. Our approach enhances state bootstrapping efficiency and reduces operational overhead by utilizing a dual-chain structure comprising a main chain and a snapshot chain. The snapshot chain periodically records key blockchain states, allowing nodes to synchronize more efficiently. This mechanism is critical in reducing the time and resources needed for new nodes to join the network or existing nodes to recover from outages. Additionally, a block state pruning technique is implemented, significantly minimizing storage requirements and lowering transaction execution overhead during initialization and reconfiguration processes. This is crucial given the substantial data volumes inherent in IoMT ecosystems. By adopting an optimistic sharding strategy, our model allows nodes to swiftly join the snapshot shard, while full shards retain the complete ledger history to ensure comprehensive transaction verification. Extensive evaluations across diverse shard configurations demonstrate that this method significantly outperforms existing baseline models. It provides a comprehensive solution for IoMT blockchain applications, striking an optimal balance between security, scalability, and operational efficiency.

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Keywords

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