计算机科学
云计算
调度(生产过程)
边缘计算
钥匙(锁)
资源(消歧)
系统集成
知识库
共享资源
系统工程
任务(项目管理)
数据共享
资源配置
数据集成
智慧城市
大数据
资源管理(计算)
互联网
物联网
云制造
数据科学
过程管理
任务分析
决策支持系统
分布式计算
数据处理
资源效率
边缘设备
控制(管理)
智能系统
智能决策支持系统
GSM演进的增强数据速率
智能制造
信息系统
系统体系结构
工程类
作者
Xuehan Li,Tao Jing,Yang Wang,Bo Gao,Jing Ai,Minghao Zhu
标识
DOI:10.32604/cmc.2026.075426
摘要
With the deep integration of cloud computing, edge computing and the Internet of Things (IoT) technologies, smart manufacturing systems are undergoing profound changes. Over the past ten years, an extensive body of research on cloud-edge-end systems has been generated. However, challenges such as heterogeneous data fusion, real-time processing and system optimization still exist, and there is a lack of systematic review studies. In this paper, we review a cloud-edge-end collaborative sensing-communication-computing-control (SC3) system. This system integrates four layers of sensing, communication, computing and control to address the complex challenges of real-time decision making, resource scheduling and system optimization. The paper combs through the key implementation methods of intelligent sensing, data preprocessing, task offloading and resource allocation in this system, and analyzes their advantages and disadvantages. On this basis, feasible methods for overall system optimization are further explored. Finally, the paper summarizes the main challenges facing the deep integration of cloud-edge-end and proposes prospective research directions, providing a structured knowledge base and development framework for subsequent research. The paper aims to stimulate further exploration of multilevel collaborative mechanisms for smart manufacturing systems to enhance the real-time decision-making and overall performance of the smart manufacturing system.
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