Year: 2025
Type: conference-paper
Abstract: In the analysis of education big data based on SDN architecture, in order to allocate server resources reasonably to different application requests of learners. We need reliable and adaptive educational resource management strategies to automatically extract and organize fragmented information in real-time, in order to obtain positive and effective information. This project focuses on the research of education big data analysis under SDN architecture. It mainly includes the following four aspects:First, Algorithms and models for educational big data analysis: Focus on researching various deep learning algorithms and globally optimized big data analysis functional models. Second, Optimizing SDN architecture to serve education big data analysis: The focus is on researching a highly scalable and integrated SDN architecture that can effectively serve the quality of education big data analysis. Third, Ensure fault-tolerant computing in education big data analysis: Focus on researching the automation management of global network resources, identify various problems, and avoid risks to ensure education big data analysis services. Fourth, Multi objective optimization for online learning: Research on multi-objective optimization analysis of educational big data based on typical applications of large-scale cloud SDN.
Authors: Pingfang Hu, Chun Wang
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4413845117