Research on Actwill Data Migration Services Based on SDN
Keywords:
SDN, AWS, Disaster recovery, Network model, Data migration, Application clusterAbstract
SDN (Software Defined Network) is an emerging network design concept that breaks the architecture of traditional networks and introduces a new network architecture featuring centralized software management, programmability, and separation of control and forwarding planes. SDN represents a technological innovation and a new network philosophy, addressing the incompatibility and complex forwarding issues of traditional networks. At the same time, a variety of technologies have been derived from this technology. This paper presents research and analysis conclusions on data migration service technologies based on SDN.
References
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.
Su, Tian, et al. "Anomaly Detection and Risk Early Warning System for Financial Time Series Based on the WaveLST-Trans Model." (2025).
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.
Wang, Hao. "Joint Training of Propensity Model and Prediction Model via Targeted Learning for Recommendation on Data Missing Not at Random." AAAI 2025 Workshop on Artificial Intelligence with Causal Techniques. 2025.
Ding, C.; Wu, C. Self-Supervised Learning for Biomedical Signal Processing: A Systematic Review on ECG and PPG Signals. medRxiv 2024.
Zhang, Yuhan. "InfraMLForge: Developer Tooling for Rapid LLM Development and Scalable Deployment." (2025).
Hu, Xiao. "GenPlayAds: Procedural Playable 3D Ad Creation via Generative Model." (2025).
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. "ProtoMind: Modeling Driven NAS and SIP Message Sequence Modeling for Smart Regression Detection." (2025).
Xie, Minhui, and Boyan Liu. "InspectX: Optimizing Industrial Monitoring Systems via OpenCV and WebSocket for Real-Time Analysis." (2025).
Zhu, Bingxin. "REACTOR: Reliability Engineering with Automated Causal Tracking and Observability Reasoning." (2025).
Zhang, Yuhan. "AdOptimizer: A Self-Supervised Framework for Efficient Ad Delivery in Low-Resource Markets." (2025).
Hu, Xiao. "Low-Cost 3D Authoring via Guided Diffusion in GUI-Driven Pipeline." (2025).
Tan, C., Gao, F., Song, C., Xu, M., Li, Y., & Ma, H. (2024). Highly Reliable CI-JSO based Densely Connected Convolutional Networks Using Transfer Learning for Fault Diagnosis.
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.
Yang, J. (2025, July). Identification Based on Prompt-Biomrc Model and Its Application in Intelligent Consultation. In Innovative Computing 2025, Volume 1: International Conference on Innovative Computing (Vol. 1440, p. 149). Springer Nature.
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Copyright (c) 2025 Chengliang Zhao, Binhui Tang
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
