survey

Blockchain Data Storage Optimisations: A Comprehensive Survey

Authors:

Gowri Sankar Ramachandran,

Raja JurdakAuthors Info & Claims

ACM Computing Surveys, Volume 56, Issue 7

Article No.: 179, Pages 1 - 27

https://doi.org/10.1145/3645104

Published: 09 April 2024 Publication History

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.

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Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 56, Issue 7

July 2024

1006 pages

EISSN:1557-7341

DOI:10.1145/3613612

Editors:
David Atienza
Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland
,
Michela Milano
University of Bologna, Italy

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Publication History

Published: 09 April 2024

Online AM: 08 February 2024

Accepted: 31 January 2024

Revised: 17 December 2023

Received: 07 September 2022

Published in CSUR Volume 56, Issue 7

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