Architecture Design and Performance Analysis of MPLS VPN in Meteorological Wide-Area Networks
Keywords:
MPLS VPN, Meteorological Network, Network Architecture, Data Transmission, Weather Forecasting, Mesh Network, Network StabilityAbstract
The continuous advancement of meteorological observation technologies has led to an exponential growth in data volume, necessitating highly efficient and robust data transmission networks to improve forecasting accuracy and timeliness. Concurrently, meteorological services are undergoing a strategic shift towards intensification and structural flattening to enhance operational responsiveness. However, the conventional three-tier (provincial-municipal-county) tree-structured network architecture has emerged as a critical bottleneck, characterized by inherent latency and single points of failure that impede data flow and service agility. To address these limitations, this paper proposes and describes the implementation of a Multi-Protocol Label Switching (MPLS) Virtual Private Network (VPN) architecture to reconstruct the foundational meteorological network. This modernized design establishes a secure, three-layer mesh network that enables logical direct connectivity between any two nodes across the administrative hierarchy. The results demonstrate that this MPLS VPN-based mesh topology significantly enhances the stability, reliability, and data transmission efficiency of the meteorological private network. By facilitating seamless, low-latency communication and providing robust traffic engineering capabilities, this network transformation effectively supports the evolving demands of data-intensive and time-sensitive modern meteorological operations, paving the way for more advanced and reliable weather prediction services.
References
Peng, Qucheng, Ce Zheng, and Chen Chen. "A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024.
Peng, Qucheng, et al. "RAIN: regularization on input and network for black-box domain adaptation." Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. 2023.
Pinyoanuntapong, Ekkasit, et al. "Gaitsada: Self-aligned domain adaptation for mmwave gait recognition." 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS). IEEE, 2023.
Zheng, Ce, et al. "Diffmesh: A motion-aware diffusion framework for human mesh recovery from videos." 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025.
Wang, Z., Chew, J. J., Wei, X., Hu, K., Yi, S., & Yi, S. (2025). An Empirical Study on the Design and Optimization of an AI-Enhanced Intelligent Financial Risk Control System in the Context of Multinational Supply Chains. Journal of Theory and Practice in Economics and Management, 2(2), 49–62. Retrieved from https://woodyinternational.com/index.php/jtpem/article/view/208
Q. Tian, D. Zou, Y. Han and X. Li, "A Business Intelligence Innovative Approach to Ad Recall: Cross-Attention Multi-Task Learning for Digital Advertising," 2025 IEEE 6th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), Shenzhen, China, 2025, pp. 1249-1253, doi: 10.1109/AINIT65432.2025.11035473.
Chen, Yinda, et al. "Generative text-guided 3d vision-language pretraining for unified medical image segmentation." arXiv preprint arXiv:2306.04811 (2023).
Li, Huaxu, et al. "Enhancing Intelligent Recruitment With Generative Pretrained Transformer and Hierarchical Graph Neural Networks: Optimizing Resume-Job Matching With Deep Learning and Graph-Based Modeling." Journal of Organizational and End User Computing (JOEUC) 37.1 (2025): 1-24.
Zhang, Zongzhen, Qianwei Li, and Runlong Li. "Leveraging Deep Learning for Carbon Market Price Forecasting and Risk Evaluation in Green Finance Under Climate Change." Journal of Organizational and End User Computing (JOEUC) 37.1 (2025): 1-27.
Tong, Kejian, et al. "An Integrated Machine Learning and Deep Learning Framework for Credit Card Approval Prediction." 2024 IEEE 6th International Conference on Power, Intelligent Computing and Systems (ICPICS). IEEE, 2024.
Tan, C., Gao, F., Song, C., Xu, M., Li, Y., & Ma, H. (2024). Proposed Damage Detection and Isolation from Limited Experimental Data Based on a Deep Transfer Learning and an Ensemble Learning Classifier.
Zhuang, R. (2025). Evolutionary Logic and Theoretical Construction of Real Estate Marketing Strategies under Digital Transformation. Economics and Management Innovation, 2(2), 117-124.
Han, X., & Dou, X. (2025). User recommendation method integrating hierarchical graph attention network with multimodal knowledge graph. Frontiers in Neurorobotics, 19, 1587973.
Zhang, Jingbo, et al. "AI-Driven Sales Forecasting in the Gaming Industry: Machine Learning-Based Advertising Market Trend Analysis and Key Feature Mining." (2025).
Cheng, Ying, et al. "Executive Human Capital Premium and Corporate Stock Price Volatility." Finance Research Letters (2025): 108278.
Li, X., Wang, X., & Lin, Y. (2025). Graph Neural Network Enhanced Sequential Recommendation Method for Cross-Platform Ad Campaign. arXiv preprint arXiv:2507.08959.
Xu, Haoran. "CivicMorph: Generative Modeling for Public Space Form Development." (2025).
Tu, Tongwei. "AutoNetTest: A Platform-Aware Framework for Intelligent 5G Network Test Automation and Issue Diagnosis." (2025).
Xie, M., & Liu, B. (2025, July). InspectX: Optimizing Industrial Monitoring Systems via OpenCV and WebSocket for Real-Time Analysis. In 2025 8th International Conference on Computer Information Science and Application Technology (CISAT) (pp. 1228-1232). IEEE.
Zhu, B. (2025, August). REACTOR: Reliability Engineering with Automated Causal Tracking and Observability Reasoning. In 2025 6th International Conference on Artificial Intelligence and Electromechanical Automation (AIEA) (pp. 540-543). IEEE.
Zhang, Yuhan. "AdOptimizer: A Self-Supervised Framework for Efficient Ad Delivery in Low-Resource Markets." (2025).
Hu, X. (2025, July). Low-Cost 3D Authoring via Guided Diffusion in GUI-Driven Pipeline. In 2025 8th International Conference on Computer Information Science and Application Technology (CISAT) (pp. 152-156). IEEE.
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