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ARTICLE
An Improved Blockchain-Empowered Storage Service Based on Data Association
1 State Grid Information & Communication Company of Hunan Electric Power Corporation, Hunan Provincial Key Laboratory of Internet of Things in Electricity, Changsha, China
2 School of Computer Science and Technology, Changsha University of Science and Technology, Changsha, China
* Corresponding Author: Jingyu Zhang. Email:
(This article belongs to the Special Issue: AI-Driven Optimization for Secure and Sustainable Edge IoT Services)
Computers, Materials & Continua 2026, 88(2), 69 https://doi.org/10.32604/cmc.2026.080210
Received 04 February 2026; Accepted 28 April 2026; Issue published 15 June 2026
Abstract
The integration of Internet of Things (IoT) with blockchain technology introduces significant challenges in handling massive and frequent transaction data generated by distributed IoT devices. The Unspent Transaction Output (UTXO) model, widely adopted in blockchain systems like Bitcoin, faces critical scalability issues when applied to IoT environments. This is because the datasets it processes expand rapidly, which consumes a large amount of memory and increases the disk access latency of resource-constrained IoT nodes. Existing optimization approaches exhibit limitations in dynamic adaptability and protocol compatibility. To address these challenges, we propose an improved blockchain-empowered storage service that introduces a data association-based multi-zone storage framework for UTXO-based blockchain systems. This service establishes a predictive model for UTXO access probability by analyzing IoT device transaction time intervals and address-specific frequencies. Subsequently, we design a dynamic three-zone storage framework that intelligently optimizes UTXO placement. Experimental results demonstrate that our approach significantly reduces disk access and optimizes memory usage compared with prevalent algorithms, while maintaining compatibility with existing UTXO-based protocols.Keywords
Cite This Article
Copyright © 2026 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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