基于数据可用性采样与智能合约的去中心化存储方法

doi:10.19678/j.issn.1000-3428.0070289

摘要/Abstract

摘要：

去中心化存储具有高可用性和强扩展性, 但由于数据分散存储在多个节点上, 存在数据存取速度慢、操作复杂等问题, 用户体验相比中心化存储较差。为此, 利用数据可用性采样技术, 在保持方法去中心化特性的同时, 融合中心化存储的优势。在数据可用性采样技术中, 多个节点从单个数据拥有者处获取随机选取的规模较小的数据子集, 其常与纠删码结合使用来提高数据可用性。基于数据可用性采样技术, 引入去中心化的存储提供者, 以单对单的形式为用户提供服务, 同时利用数据保障者来监督存储提供者并为用户数据提供保障。设计一套较为完备的存储方法, 来实现高可用的数据存储, 并利用区块链与智能合约来增强其去中心化程度。通过支持再质押模式, 并采用低计算资源消耗的存储证明算法, 来提高节点的加入意愿。为解决较大的数据规模与数据保障者有限的带宽资源之间的矛盾, 提出延迟确认机制。实验与分析结果表明, 在该方法下, 恶意节点共谋概率仅为2.43×10^-3, 数据可用性采样结果不可信的概率仅为2.93×10^-4, 在300万次模拟实验中发生数据不可用的次数为0, 中心化节点数为0, 为1 MiB大小的文件生成存储证明仅需3.51 ms。该方法在提高用户友好性和节点友好性的同时, 实现了高可用的数据存储, 为优化去中心化存储提供了可行的技术路径。

关键词: 数据可用性采样, 区块链, 智能合约, 去中心化存储, 纠删码

Abstract:

Decentralized storage offers high availability and scalability. However, owing to the decentralized storage of data across multiple nodes, issues such as slow data access and complex operations arise, resulting in a poorer user experience compared to centralized storage. To address this, a data availability sampling technology is employed, which maintains the decentralized nature of the method while incorporating the advantages of centralized storage. In data availability sampling technology, multiple nodes obtain a smaller, randomly selected subset of data from a single data owner. This technology is often combined with erasure coding to enhance data availability. Based on data availability sampling technology, decentralized storage providers are introduced to serve users on a one-to-one basis, and data guarantors supervise storage providers and provide guarantees for user data. A comprehensive storage method is designed to achieve highly available data storage, and blockchain and smart contracts are employed to enhance decentralization. By supporting a repledging model and adopting a storage-proof algorithm with low computational resource consumption, the willingness of the nodes to join is increased. To resolve the contradiction between large data scales and the limited bandwidth resources of data guarantors, a delayed confirmation mechanism is proposed. Experimental and analytical results show that under this method, the probability of malicious node collusion is only 2.43×10^-3, the probability of untrustworthy data availability sampling results is only 2.93×10^-4, the number of data unavailability occurrences is 0 in 3 million simulation experiments, the number of centralized nodes is 0, and generating storage proofs for a 1 MiB file takes only 3.51 ms. This method achieves highly available data storage while improving user-friendliness and node-friendliness, providing a feasible technical path for optimizing decentralized storage.

Key words: data availability sampling, blockchain, smart contract, decentralized storage, erasure code

陈中, 李晓风, 赵赫, 张凌浩. 基于数据可用性采样与智能合约的去中心化存储方法[J]. 计算机工程, 2026, 52(6): 189-201.

CHEN Zhong, LI Xiaofeng, ZHAO He, ZHANG Linghao. Decentralized Storage Method Based on Data Availability Sampling and Smart Contracts[J]. Computer Engineering, 2026, 52(6): 189-201.

https://www.ecice06.com/CN/Y2026/V52/I6/189

图/表 12

图1 本文方法系统框架

Fig.1 System framework of the method in this paper

图2 数据保障机制

Fig.2 Data assurance mechanism

图3 一对多纠删码编码流程

Fig.3 The process of one-to-many erasure coding

图4 数据存储交易流程

Fig.4 The process of data storage transaction

图5 延迟确认机制流程

Fig.5 The process of the delayed confirmation mechanism

图6 托管服务商存储成本降低比例

Fig.6 Reduction ratio of storage cost for hosting service providers

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