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e-Learning, e-Education, and Online Training. 8th EAI International Conference, eLEOT 2022, Harbin, China, July 9–10, 2022, Proceedings, Part I

Research Article

Music Distance Education Resource Sharing Method Based on Big Data Platform

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-21161-4_52,
        author={Jun Zhou and Hui Lin},
        title={Music Distance Education Resource Sharing Method Based on Big Data Platform},
        proceedings={e-Learning, e-Education, and Online Training. 8th EAI International Conference, eLEOT 2022, Harbin, China, July 9--10, 2022, Proceedings, Part I},
        proceedings_a={ELEOT},
        year={2023},
        month={3},
        keywords={Big data platform Music distance education Resource sharing Shared weight Iaas structure Openstack scheduling strategy},
        doi={10.1007/978-3-031-21161-4_52}
    }
    
  • Jun Zhou
    Hui Lin
    Year: 2023
    Music Distance Education Resource Sharing Method Based on Big Data Platform
    ELEOT
    Springer
    DOI: 10.1007/978-3-031-21161-4_52
Jun Zhou1,*, Hui Lin1
  • 1: College of Art, Xinyu University
*Contact email: zhoujun11234@126.com

Abstract

In order to promote the rapid transmission of music distance education resources, so that students can obtain more shared data information in unit time. This paper proposes a resource sharing method for music distance education based on the big data platform. According to the connection form of the big data platform architecture, determine the function capability of the virtualization sharing technology. Then, by calculating the shared weight of educational resources, the farthest transmission distance of music distance education resources in the network environment is constrained. Complete the relevant application technology analysis based on the big data platform. On this basis, construct the IaaS resource sharing structure. Combined with the established OpenStack scheduling policy, the statistical numerical indicators of shared access are calculated. To realize the smooth application of the music distance education resource sharing method based on the big data platform. The experimental results show that under the action of this new sharing method, the total value of shared data information obtained by students in unit time increases significantly. The method can promote the rapid transmission of music distance education resources, and meet the needs of practical applications.

Keywords
Big data platform Music distance education Resource sharing Shared weight Iaas structure Openstack scheduling strategy
Published
2023-03-09
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-21161-4_52
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