区块链支持的去中心化服务选择,用于服务质量感知云制造

IF 3 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Expert Systems Pub Date : 2024-05-10 DOI:10.1111/exsy.13602
Ke Meng, Zhiyong Wu, Muhammad Bilal, Xiaoyu Xia, Xiaolong Xu
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引用次数: 0

摘要

近年来,云制造给制造业带来了机遇和挑战。云制造实现了全球制造资源的统一和共享,打破了地域限制,提高了制造水平和效率。然而,随着制造资源和用户需求的爆发式增长,传统的云制造平台在服务选择过程中会面临计算能力不足、实时数据缺乏、用户隐私难以保障等问题。本文提出了一种基于区块链的去中心化云制造服务选择方法,将计算资源部署在多个分布式节点上,而非传统的中心化云制造平台,以解决计算能力不足的问题。根据用户在合约上的表现来评估用户的可信度,并根据用户的可信度改进 PBFT 共识算法。此外,还设计了三链区块链数据存储模型,以确保云制造服务选择过程中数据的安全性、实时性和透明性。实验结果表明,该方法既加快了服务选择过程,又提高了服务选择结果的质量,实现了制造效率的显著提升。
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Blockchain‐enabled decentralized service selection for QoS‐aware cloud manufacturing
In recent years, cloud manufacturing has brought both opportunities and challenges to the manufacturing industry. Cloud manufacturing enables global manufacturing resources to be unified and shared, thus breaking down geographical constraints to enhance the level and efficiency of manufacturing. However, with the explosive growth of manufacturing resources and user demands, traditional cloud manufacturing platforms will face problems of insufficient computility, lack of real‐time data and difficulties in securing user privacy during the service selection process. In this article, a blockchain‐based decentralized cloud manufacturing service selection method is proposed, where the computility resource is deployed in multiple distributed nodes rather than the traditional centralized cloud manufacturing platform to solve the problem of insufficient computility. The credibility of the users is evaluated based on their performance on the contract and the PBFT consensus algorithm is improved based on the credibility of the users. In addition, a tri‐chain blockchain data storage model is designed to ensure the security, real‐time and transparency of data in the cloud manufacturing service selection process. The experimental results show that the method both speeds up service selection process and improves the quality of service selection results, and achieves a significant increase in manufacturing efficiency.
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来源期刊
Expert Systems
Expert Systems 工程技术-计算机:理论方法
CiteScore
7.40
自引率
6.10%
发文量
266
审稿时长
24 months
期刊介绍: Expert Systems: The Journal of Knowledge Engineering publishes papers dealing with all aspects of knowledge engineering, including individual methods and techniques in knowledge acquisition and representation, and their application in the construction of systems – including expert systems – based thereon. Detailed scientific evaluation is an essential part of any paper. As well as traditional application areas, such as Software and Requirements Engineering, Human-Computer Interaction, and Artificial Intelligence, we are aiming at the new and growing markets for these technologies, such as Business, Economy, Market Research, and Medical and Health Care. The shift towards this new focus will be marked by a series of special issues covering hot and emergent topics.
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