Edge Intelligence: Edge Computing for 5G and the Internet of Things, 2nd Edition
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 583
Special Issue Editors
Interests: mobile computing; data privacy; machine learning (artificial intelligence); internet of things
Special Issues, Collections and Topics in MDPI journals
Interests: edge computing; edge intelligence; 5G/6G; IoT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
To enhance 5G and IoT networks with AI capabilities, large volumes of multi-modal sensing data (e.g., audio and video) are continuously generated by mobile and IoT devices located at the network edge. Driven by this trend, there is an urgent need to advance AI at the network edge to fully unlock the potential utilization of 5G and IoT networks for various smart services and applications. Thus, edge intelligence, an emerging paradigm that pushes AI tasks and services from the network core to the network edge, is increasingly recognized as a crucial component of next-generation intelligent networking systems. Research on edge intelligence is still in its preliminary stages; thus, a dedicated platform for the discussion, promotion, and dissemination of research in this field is highly desired by the networking, computing, and AI communities. To address this gap, this Special Issue aims to gather recent advances and novel contributions from academic researchers and industry practitioners in the areas of edge intelligence and edge computing for 5G and IoT networks. The scope of this Special Issue includes, but is not limited to, the following topics:
- Intelligent edge computing resource management for 5G/B5G/6G and IoT;
- Edge computing system and AI model co-design for 5G/B5G/6G and IoT;
- Cloud–edge–device converged computing for AI for 5G/B5G/6G and IoT;
- Federated edge learning over for 5G/B5G/6G and IoT;
- Distributed edge intelligence model training and inference;
- Privacy-preserving methods for edge intelligence;
- Large edge models and their applications for 5G/B5G/6G and IoT;
- Distributed edge data analytics for 5G/B5G/6G and IoT;
- Other emerging edge computing and edge intelligence techniques and applications for 5G/B5G/6G and IoT.
Dr. Yuezhi Zhou
Prof. Dr. Xu Chen
Guest Editors
Manuscript Submission Information
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Keywords
- edge computing
- edge intelligence
- edge large models
- 5G/B5G/6G networks
- IoT networks
- federated edge learning
- cloud-edge-device converged computing
- distributed edge intelligence model training and inference
- privacy-preserving edge intelligence
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