Big Model Mobile Edge Computing: The Fusion Paradigm of Next-Generation Generative Edge Computing
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 80
Editor
Interests: social networks and social applications; computational-data-mining reinforcement learning; multi-agent systems and autonomous agents; opinion dynamics
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Special Issue Information
Dear Colleagues,
The integration of Mobile Edge Computing (MEC) technology with the medical domain is revolutionizing the healthcare industry, while also catalyzing a wave of technological innovation in the industrial sector. With the digital transformation and technological innovations in both the medical and industrial fields, the fusion of MEC with Big Model (BM) technologies is presenting unprecedented opportunities and challenges for these two domains.
Firstly, with the widespread adoption of medical devices, sensors, and monitors, as well as the increasing intelligence of industrial equipment, a large amount of real-time data is being generated and collected. The combination of MEC and BM technology enables this data to be processed and analyzed near the devices in real-time, providing faster and more intelligent support for medical and industrial decision-making. The powerful data processing capabilities of BMs facilitate in-depth analysis of medical and industrial data, offering precise support for clinical and production decisions. Furthermore, MEC enhances the efficiency and reliability of medical and industrial services by reducing data transmission and processing latency. In emergency and urgent situations, MEC enables critical data to be instantly transmitted to medical professionals or industrial operators, thereby shortening response times. The integration of BMs further improves the accuracy and efficiency of diagnosis, treatment, and production, providing higher quality services for patients and production lines. Moreover, the industrial sector can utilize personalized production data to optimize production processes, enhance production efficiency, and improve product quality. However, considering the distinct characteristics of the medical and industrial domains, the integration of MEC technology with BMs also faces some common challenges, such as data security and privacy protection, device interoperability, and system reliability. Therefore, further research and exploration are necessary to achieve a balance in the medical and industrial domains, fully leveraging MEC and BM technologies to optimize services, address challenges, and drive both domains towards intelligent, efficient, and personalized directions. Potential topics of interest include, but are not limited to, the following:
- The Application of MEC and BM Fusion Technology in Medical Data Analysis and Privacy Protection
- MEC and BM Enabled Remote Healthcare and Emergency Rescue Services
- The Application of MEC and BMs in Interconnected Healthcare Facilities and Intelligent Management
- Intelligent Medical Devices and Sensor Networks Supported by MEC and BMs
- Personalized Healthcare and Health Monitoring Solutions Based on MEC and BMs
- The Application of MEC and BMs in the Internet of Medical Things (IoMT)
- Personalized Healthcare Services Driven by MEC and BMs
- Edge Analysis and Processing of Healthcare Data Enabled by MEC and BMs
- Real-time Monitoring and Response in Healthcare and Industrial Settings Supported by MEC and BMs
- The Application of MEC and BMs in Industrial Data Analysis and Privacy Protection
- MEC and BM Applications in Industrial Internet of Things (IIoT)
- Integration of MEC and BMs in Interconnected and Intelligent Management of Industrial Facilities
- Data Security and Privacy Protection Mechanisms in Industrial Environments
- Optimization and Real-time Data Processing in IIoT Enabled by MEC and BMs
- The Application of MEC and BMs in Industrial Safety Monitoring and Risk Management
Dr. Qiang He
Guest Editor
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Keywords
- multi-access edge computing (MEC)
- blockchain mechanisms (BM)
- federated learning
- edge intelligence
- 5G/6G networks
- digital twins
- internet of things (IoT)
- privacy-preserving data fusion
- secure multi-party computation
- access control
- internet of medical things (IoMT)
- health data analytics
- industrial internet of things (IIoT)
- risk management
- supply chain transparency
- real-time edge analytics
- low-latency data processing
- time-series forecasting
- edge-cloud continuum
- AI-driven optimization
- big data in IoT
- human-centric computing
- game theory for security
- green edge computing
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