Data-driven approach for selection of on-chain vs off-chain carbon credits data storage methods

Alghanmi, NA; Alghanmi, NA; Alghanmi, SA; Zhao, M; Hussain, FK

Data-driven approach for selection of on-chain vs off-chain carbon credits data storage methods

Alghanmi, NA Alghanmi, NA Alghanmi, SA Zhao, M

Hussain, FK

Permalink

Publisher:: Elsevier
Publication Type:: Journal Article
Citation:: Knowledge-Based Systems, 2024, 310, pp. 112871
Issue Date:: 2024-12

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Accepted versionAdobe PDF (2.54 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Alghanmi, NA
dc.contributor.author	Alghanmi, NA
dc.contributor.author	Alghanmi, SA
dc.contributor.author	Zhao, M https://orcid.org/0000-0002-7267-2119
dc.contributor.author	Hussain, FK
dc.date.accessioned	2025-03-03T04:12:50Z
dc.date.available	2025-03-03T04:12:50Z
dc.date.issued	2024-12
dc.identifier.citation	Knowledge-Based Systems, 2024, 310, pp. 112871
dc.identifier.issn	0950-7051
dc.identifier.uri	http://hdl.handle.net/10453/185494
dc.description.abstract	As blockchain technology continues to revolutionize various industries, the efficient and secure storage of data has become a critical challenge. Inspired by blockchain s distributed peer-to-peer networks, security and information storage solutions have found widespread application in high-information environments due to their efficiency, security, traceability, and decentralized nature. However, as blockchain applications expand and the volume of data grows exponentially, the interplay between on-chain and off-chain storage is rapidly becoming a crucial factor in blockchain data management. The motivation for this research stems from the pressing need to address the scalability and performance issues inherent in blockchain systems as they handle increasingly large datasets. Carbon credits data, specifically from a provenance perspective, is multimodal in nature. It can be captured using many different modes and devices and could include images, text, and unstructured data. Current literature lacks a comprehensive analysis of the trade-offs between on-chain and off-chain storage methods, particularly for multimedia data, in terms of their impact on system scalability, operational efficiency, and economic viability. This gap in knowledge hinders stakeholders from making informed decisions about optimal data disposition strategies for their blockchain implementations. This paper aims to bridge this gap by delivering a comprehensive explanation of the data storage methods adopted by blockchain systems, focusing on scalability, efficiency, and economic viability as key evaluation criteria. We analyze the unique connotations and implications of both on-chain and off-chain storage, considering their effects on data retrieval times and overall system performance. Through our analysis, we derive valuable insights to guide the decision-making process in designing and implementing blockchain solutions tailored to specific needs and application scenarios. By providing a thorou
dc.language	en
dc.publisher	Elsevier
dc.relation.ispartof	Knowledge-Based Systems
dc.relation.isbasedon	10.1016/j.knosys.2024.112871
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	08 Information and Computing Sciences, 15 Commerce, Management, Tourism and Services, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	4602 Artificial intelligence
dc.subject.classification	4605 Data management and data science
dc.subject.classification	4611 Machine learning
dc.title	Data-driven approach for selection of on-chain vs off-chain carbon credits data storage methods
dc.type	Journal Article
utslib.citation.volume	310
utslib.for	08 Information and Computing Sciences
utslib.for	15 Commerce, Management, Tourism and Services
utslib.for	17 Psychology and Cognitive Sciences
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Australian Artificial Intelligence Institute (AAII)
utslib.copyright.status	open_access	*
pubs.consider-herdc	true
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.date.updated	2025-03-03T04:12:48Z
pubs.publication-status	Published
pubs.volume	310

Abstract:

As blockchain technology continues to revolutionize various industries, the efficient and secure storage of data has become a critical challenge. Inspired by blockchain s distributed peer-to-peer networks, security and information storage solutions have found widespread application in high-information environments due to their efficiency, security, traceability, and decentralized nature. However, as blockchain applications expand and the volume of data grows exponentially, the interplay between on-chain and off-chain storage is rapidly becoming a crucial factor in blockchain data management. The motivation for this research stems from the pressing need to address the scalability and performance issues inherent in blockchain systems as they handle increasingly large datasets. Carbon credits data, specifically from a provenance perspective, is multimodal in nature. It can be captured using many different modes and devices and could include images, text, and unstructured data. Current literature lacks a comprehensive analysis of the trade-offs between on-chain and off-chain storage methods, particularly for multimedia data, in terms of their impact on system scalability, operational efficiency, and economic viability. This gap in knowledge hinders stakeholders from making informed decisions about optimal data disposition strategies for their blockchain implementations. This paper aims to bridge this gap by delivering a comprehensive explanation of the data storage methods adopted by blockchain systems, focusing on scalability, efficiency, and economic viability as key evaluation criteria. We analyze the unique connotations and implications of both on-chain and off-chain storage, considering their effects on data retrieval times and overall system performance. Through our analysis, we derive valuable insights to guide the decision-making process in designing and implementing blockchain solutions tailored to specific needs and application scenarios. By providing a thorou

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/185494