Storage Scalability Oriented Segment Allocation Based on Cost Clustering in Sharding Blockchains

IF 3.9 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Liping Tao;Yang Lu;Yuqi Fan;Lei Shi;Zhen Wei
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引用次数: 0

Abstract

Blockchain technology has garnered significant attention from academia and industry, with scalability remaining a key challenge. Sharding is a promising solution, dividing the blockchain into smaller partitions called shards, each processing a portion of the transactions to increase throughput. This approach is critical for enabling efficient Proof of Stake (PoS) consensus mechanisms, as demonstrated by the transition of Dogecoin to PoS, where sharding reduces the computational burden on validators and enhances scalability. However, sharding introduces high storage redundancy, as nodes in each shard must collectively maintain a copy of the entire blockchain, imposing substantial storage pressure. To address this, segments are introduced to divide the main chain into smaller parts distributed across nodes. Existing methods, however, randomly assign segments to nodes, resulting in high costs for node setup and segment queries. This paper investigates the optimal allocation of segments within shards to minimize these costs, proposing a Segment Allocation algorithm based on Cost Clustering (SACC). Theoretical analysis and simulations demonstrate that SACC achieves lower setup, query, and total costs while maintaining security and scalability, offering a more efficient solution for sharding-based PoS blockchains like Dogecoin.
分片区块链中基于成本聚类的面向存储可扩展性的段分配
区块链技术已经引起了学术界和工业界的极大关注,但可伸缩性仍然是一个关键挑战。分片是一种很有前途的解决方案,它将区块链划分为更小的分区,称为分片,每个分区处理一部分事务以提高吞吐量。这种方法对于实现有效的权益证明(PoS)共识机制至关重要,正如狗狗币向PoS的过渡所证明的那样,其中分片减少了验证者的计算负担并增强了可扩展性。然而,分片引入了高存储冗余,因为每个分片中的节点必须共同维护整个区块链的副本,从而施加了巨大的存储压力。为了解决这个问题,引入了分段,将主链划分为分布在节点上的更小的部分。然而,现有的方法随机地将段分配给节点,导致节点设置和段查询的成本很高。本文研究了分片内分片的最佳分配,以最小化这些成本,提出了一种基于成本聚类(SACC)的分片分配算法。理论分析和仿真表明,SACC在保持安全性和可扩展性的同时,实现了更低的设置、查询和总成本,为狗狗币等基于分片的PoS区块链提供了更有效的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Sustainable Computing
IEEE Transactions on Sustainable Computing Mathematics-Control and Optimization
CiteScore
7.70
自引率
2.60%
发文量
54
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