Service Composition and Optimal Selection in Cloud Manufacturing: State-of-the-Art and Research Challenges

Author:

Alinani KarimORCID,Liu Deshun,Zhou DongORCID,Wang GuojunORCID

Funder

National Natural Science Foundation of China

Guangdong Provincial Natural Science Foundation

High-Level Talents Program of Higher Education in Guangdong Province

Hunan Education Department Excellent Youth Project

Scientific Research Fund of Hunan Provincial Education Department

Postdoctoral Funding of the Hunan University of Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimizing Edge-Cloud Server Selection: A Multi-Objective Deep Reinforcement Learning Approach;2024 IEEE Cloud Summit;2024-06-27

2. Energy-aware cloud manufacturing service selection and scheduling optimization;International Journal of Computer Integrated Manufacturing;2024-03-24

3. Task Decomposition and Service Composition on an Innovative Blockchain-Based Construction Service Trading Platform to Select Construction Services;Journal of Construction Engineering and Management;2023-12

4. Heuristic-Based Service Allocation and Price Determination in Cloud Manufacturing Operations for Industrial Parks;2023 IEEE 19th International Conference on Automation Science and Engineering (CASE);2023-08-26

5. A New Cloud Resource Manufacturing System Based on the Internet of Things Using Optimized Deep Neural Network;2023 1st International Conference on Cognitive Computing and Engineering Education (ICCCEE);2023-04-27

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