Online allocation algorithm of digital story course resources based on deep learning

Ke Xu; Julina Ismail Kamal

doi:10.1117/12.2660269

22 November 2022 Online allocation algorithm of digital story course resources based on deep learning

Ke Xu, Julina Ismail Kamal

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 1247522 (2022) https://doi.org/10.1117/12.2660269
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

The online allocation of course resources is a part of the field of cloud computing. Studying the allocation of digital story course resources through cloud computing architecture can not only meet the requirements of cloud computing resource allocation, but also improve the utilization efficiency of digital story course resources. This paper mainly proposes an application-oriented resource allocation algorithm based on deep learning. This online allocation algorithm mainly quantifies the characteristics of the data, and more accurately creates the server resources required by the digital story course. In addition, the workload prediction model is integrated into the online allocation algorithm, which can Ensure that curriculum resources and teaching are more matched, so as to give full play to the value of resource use.

Citation Download Citation

Ke Xu and Julina Ismail Kamal "Online allocation algorithm of digital story course resources based on deep learning", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 1247522 (22 November 2022); https://doi.org/10.1117/12.2660269

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KEYWORDS

Clouds

Data modeling

Video

Computer architecture

Convolution

Data communications

Data processing

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