Intelligent Cloud–Edge Computing Continuum for Industry 4.0
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".
Deadline for manuscript submissions: 15 February 2026 | Viewed by 61
Special Issue Editors
Interests: edge computing; service computing; mobile computing
Interests: edge computing; service computing; artificial Intelligence
Special Issue Information
Dear Colleagues,
Industry 4.0 transforms manufacturing through intelligent, interconnected production systems. Cloud computing and edge computing provide the essential infrastructure for this digital transformation, enabling real-time data processing, intelligent decision-making, and seamless industrial connectivity. Specifically, cloud computing offers scalable resources for big data analytics, AI model training, and enterprise integration. It supports digital twins, collaborative manufacturing networks, and massive data storage. However, cloud-only solutions struggle with latency-sensitive industrial applications requiring immediate response times. Edge computing addresses these limitations by processing data near industrial devices and sensors. This proximity enables millisecond response times essential for autonomous control, predictive maintenance, and quality assurance. Edge computing also provides operational resilience during network disruptions and reduces bandwidth requirements. Thus, the cloud–edge synergy creates a distributed computational continuum supporting diverse Industry 4.0 needs. This hybrid architecture intelligently distributes workloads—processing time-critical operations at the edge while handling complex analytics in the cloud—enabling smart factories and autonomous manufacturing systems.
This Special Issue seeks high-quality research contributions that advance the state-of-the-art in cloud and edge computing technologies specifically tailored for Industry 4.0 applications. We welcome theoretical innovations, practical implementations, and comprehensive surveys that demonstrate how these computing paradigms can effectively support the digital transformation of manufacturing and industrial processes. Topics include but are not limited to the following:
- Federated learning for collaborative AI across manufacturing sites;
- Edge AI optimization and model compression techniques;
- Intelligent workload orchestration across cloud-edge continuum;
- Digital twin synchronization in distributed environments;
- 5G-enabled ultra-low latency industrial communications;
- Blockchain-based trust management for industrial IoT;
- Autonomous resource management and self-optimization systems;
- Zero-trust security frameworks for distributed industrial networks;
- Real-time anomaly detection and predictive maintenance at the edge.
Dr. Bo Li
Dr. Guangming Cui
Dr. Lu Zhao
Guest Editors
Manuscript Submission Information
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Keywords
- cloud computing
- edge computing
- Industry 4.0
- resource allocation
- service placement
- secure IoT
- smart factory
- edge AI
- industrial IoT
- real-time processing
- digital twin
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