Generative Edge Intelligence for Sensor Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 187
Special Issue Editors
Interests: green communications; mobile/multi-access edge computing and caching; federated learning; holographic communications; physical layer security; semantic communications
Special Issues, Collections and Topics in MDPI journals
Interests: integrated sensing and communication; federated learning; intelligent wireless communications and IoT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Sensor networks are rapidly evolving toward collaborative, autonomous, and context-aware systems. Recent advances in generative models, including diffusion models, generative adversarial networks, variational auto-encoders, auto-regressive models, and large foundation models, create new opportunities to push intelligence from cloud to edge. By synthesizing, completing, compressing, and semantically encoding sensor data, generative edge intelligence can enhance sensing quality, reduce communication overhead, and improve robustness under stringent latency, energy, and privacy constraints.
This Special Issue focuses on theories, algorithms, and systems that integrate generative artificial intelligence with edge computing for sensor networks and the Internet of Things. We welcome contributions on, but not limited to, the following topics:
- On-device and near-sensor training and inference, including lightweight generation, model compression, quantization, distillation, and split computing;
- Federated and distributed learning for generative models with privacy, security, and trustworthiness guarantees;
- Generative methods for anomaly detection, missing-data imputation, self-supervised representation learning, sensor calibration, and digital-twin construction;
- Semantic communication and generative coding for bandwidth-limited networks;
- Large language model for edge computing over sensor networks;
- Application studies and prototypes in smart cities, industrial Internet of Things, healthcare, robotics, and vehicular sensing.
Dr. Wanli Wen
Dr. Wenchao Xia
Guest Editors
Manuscript Submission Information
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Keywords
- generative artificial intelligence
- edge intelligence
- sensor networks
- internet of things
- diffusion models
- generative adversarial networks
- federated learning
- semantic communications
- privacy-preserving learning
- digital twins
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