Open Access

REVIEW

Cloud-Edge-End Collaborative SC³ System in Smart Manufacturing: A Survey

Xuehan Li¹, Tao Jing², Yang Wang², Bo Gao³, Jing Ai⁴, Minghao Zhu^5,*

1 School of Automation and Intelligence, Beijing Jiaotong University, Beijing, China
2 School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China
3 School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China
4 Software and Systems Research Department, China Electronic Product Reliability and Environmental Testing Research Institute, Guangzhou, China
5 School of Economics and Management, Beijing Jiaotong University, Beijing, China

* Corresponding Author: Minghao Zhu. Email:

(This article belongs to the Special Issue: Integrating Computing Technology of Cloud-Fog-Edge Environments and its Application)

Computers, Materials & Continua 2026, 87(2), 3 https://doi.org/10.32604/cmc.2026.075426

Received 31 October 2025; Accepted 09 January 2026; Issue published 12 March 2026

Abstract

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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Keywords

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