xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

2025-09-24

AI Summary

To address the challenge of integrating real-time environmental monitoring, shade-net damage detection, and computational fluid dynamics (CFD)-driven intervention in citrus protective shade-net (CUPS) systems, this paper proposes xGFabric—the first architecture leveraging private 5G network slicing to enable end-to-end, low-latency coupling between edge sensors and high-performance computing (HPC) resources. The system integrates edge-cloud cooperative transmission, real-time data scheduling, and HPC orchestration to overcome the longstanding bottleneck of bandwidth-constrained sensor networks and high-latency supercomputing. Experimental evaluation demonstrates that direct 5G-sliced connectivity from edge sensors to the HPC-based CFD simulation module reduces end-to-end latency by 62%, enabling near-real-time CFD modeling and dynamic intervention decisions. This advancement significantly improves both the timeliness and accuracy of digital agriculture environmental response.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Computer Vision: Remote Sensing / Geospatial AI
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Problem

• Coupling distributed sensor networks with centralized HPC facilities for real-time applications
• Bridging low-performance sensor data with high-latency batch processing in HPC systems
• Enabling near-real-time simulation for digital agriculture using 5G network capabilities

Innovation

• Private 5G networks for low-latency edge-HPC coupling
• End-to-end system connecting sensors to HPC facilities
• 5G network slicing enabling real-time agricultural simulation