GAM: A scalable and efficient multi-chain data sharing scheme

IF 7.4 1区管理学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information Processing & Management Pub Date : 2024-12-05 DOI:10.1016/j.ipm.2024.104004

Zihan Wu, Yuzhen Wang, Liangmin Wang

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引用次数: 0

Abstract

Multi-chain data sharing refers to cross-chain data exchange among multiple blockchains. However, existing multi-chain data sharing schemes rely on direct blockchain-to-blockchain connections to establish links among multiple chains. This leads to poor scalability and low efficiency as the number of connected blockchains increases. To address these problems, we propose GAM (Group Authorization-based Multi-chain Data Sharing) for scalable and efficient multi-chain data sharing. GAM enhances scalability by organizing users from different chains into authorized virtual groups, enabling trusted data sharing within it. To further improve efficiency, the data sharing authorization process is executed on-chain, while data transfer is based on off-chain storage. We provide a formal analysis of GAM in multi-chain scenarios and implement a proof-of-concept prototype using Hyperledger Fabric. Experimental results demonstrate that GAM is effective in reducing the execution time of multi-chain data sharing while maintaining high transaction throughput and minimal end-to-end delay.

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来源期刊

Information Processing & Management 工程技术-计算机：信息系统

CiteScore

17.00

自引率

11.60%

发文量

276

审稿时长

39 days

期刊介绍： Information Processing and Management is dedicated to publishing cutting-edge original research at the convergence of computing and information science. Our scope encompasses theory, methods, and applications across various domains, including advertising, business, health, information science, information technology marketing, and social computing. We aim to cater to the interests of both primary researchers and practitioners by offering an effective platform for the timely dissemination of advanced and topical issues in this interdisciplinary field. The journal places particular emphasis on original research articles, research survey articles, research method articles, and articles addressing critical applications of research. Join us in advancing knowledge and innovation at the intersection of computing and information science.