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Service-Chain-Driven Communication and Computing Integration Networking: A Case Study of Levee Piping Hazard
Jing Chen1,2, Lyuzhou Gao1,2, Hongquan Sun1,2
1National Institute of Natural Hazards, Ministry of Emergency Management of the People's Republic of China, Beijing 100085, China.
This study introduces a new integrated network architecture, (Com)2INet, for real-time levee piping hazard inspection. It efficiently combines sensing, transmission, and computation for emergency scenarios.
Area of Science:
- Geoscience and Remote Sensing
- Computer Science and Engineering
- Network Architecture
Background:
- Existing Computing Power Networks (CPN) struggle with coordinating cross-domain heterogeneous resources for time-sensitive tasks.
- Real-time, high-scalability solutions are needed for computationally intensive emergency response scenarios like levee piping hazard inspection.
- Current architectures lack seamless integration of sensing, transmission, and computation for rapid data processing.
Purpose of the Study:
- To propose a novel communication and computation integrated network architecture, (Com)2INet.
- To address the limitations of CPN in coordinating heterogeneous resources for emergency hazard detection.
- To enable real-time and scalable processing of remote sensing data for critical infrastructure monitoring.
Main Methods:
- Developed a (Com)2INet architecture integrating sensing, transmission, and computation phases.
- Utilized thermal infrared imagery and radiative transfer mechanisms for land surface temperature field retrieval in the sensing phase.
- Implemented a multi-path transmission mechanism for efficient data flow and a service-chained SACM algorithm for dynamic computation.
Main Results:
- Successfully integrated sensing, communication, and computation for enhanced hazard detection.
- Demonstrated the capability to retrieve land surface temperature fields for piping hazard identification.
- Achieved precise hazard identification through dynamic processing of temperature fields via the SACM algorithm.
Conclusions:
- The proposed (Com)2INet architecture effectively addresses challenges in real-time hazard detection for emergency scenarios.
- Seamless interaction between sensing, communication, and computation is crucial for time-sensitive remote sensing applications.
- The integrated framework provides a scalable and efficient solution for monitoring critical infrastructure like levees.
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