Blockchain Data Storage Optimisations: A Comprehensive Survey

Author:

Heo Jun Wook1ORCID,Ramachandran Gowri Sankar1ORCID,Dorri Ali1ORCID,Jurdak Raja1ORCID

Affiliation:

1. Queensland University of Technology, Brisbane, Australia

Abstract

Blockchain offers immutability, transparency, and security in a decentralised way for many applications, including finance, supply chain, and the Internet of Things (IoT). Due to its popularity and widespread adoption, it has started to process an enormous number of transactions, placing an ever-growing demand for storage. As the technology gains more popularity, the storage requirements of blockchain will increase, necessitating storage optimisation solutions. Proposed solutions for blockchain storage efficiency range from reducing the degree of data replication to redacting or compressing data. Each of these storage optimisation categories involves a complex interplay with the timing of blockchain data processing and mining, yet no existing survey analyses these dimensions. This article surveys the state-of-the-art blockchain storage optimisations and categorises them into replication-based, redaction-based, and content-based optimisations. Replication-based optimisations focus on reducing duplication of blockchain data shared among participants after committing data on the blockchain ledger. Redaction-based optimisations allow users to modify or delete data already committed on the ledger in various ways, while content-based optimisations compress data before or after committing it to the ledger. We analyse and evaluate these solutions in the aspects of security, decentralisation, and scalability. We present the advantages and disadvantages of the existing blockchain storage optimisations and comprehensively compare them. Additionally, we discuss the opportunities and challenges for future work to optimise blockchain storage.

Publisher

Association for Computing Machinery (ACM)

Reference103 articles.

1. Buterin's Scalability Trilemma viewed through a State-change-based Classification for Common Consensus Algorithms

2. Giuseppe Ateniese, Bernardo Magri, Daniele Venturi, and Ewerton Andrade. 2017. Redactable blockchain–or–rewriting history in Bitcoin and friends. In IEEE European Symposium on Security and Privacy (EuroS&P’17). IEEE, 111–126.

3. BxTB: cross-chain exchanges of bitcoins for all Bitcoin wrapped tokens

4. Alireza Beikverdi and JooSeok Song. 2015. Trend of centralization in Bitcoin’s distributed network. In IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD’15). IEEE, 1–6.

5. Eli Ben-Sasson, Alessandro Chiesa, Eran Tromer, and Madars Virza. 2014. Succinct Non-interactive zero knowledge for a Von Neumann architecture. In 23rd USENIX Security Symposium (USENIX Security’14). 781–796.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3