Research on SDN based Education Big Data Analysis

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.

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Publication Details

Published
2025-03-14
DOI
https://doi.org/10.1145/3746709.3746835
Primary Topic
Advanced Computing and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on SDN based Education Big Data Analysis

Chun Wang, Pingfang Hu
Advanced Computing and Algorithms
article

Research on SDN based Education Big Data Analysis

Chun Wang, Pingfang Hu
article en

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.

Wuhan Donghu University (CN)
Hubei Provincial Department of Education
Openalex Percentile: Top 70%
Advanced Computing and Algorithms
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