<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The challenge of managing information in collegiate physical education has progressively escalated, thereby amplifying the complexities inherent in the sports management domains at higher education institutions. The advent of artificial intelligence technology heralds a promising avenue for the evolution of sports management frameworks within these settings. This study delineates the development of a specialized cloud platform tailored for the management of collegiate sports, encompassing aspects such as teaching and research management, quality assurance in education, general teaching affairs, practical instruction, and support for auxiliary teaching processes. This platform is engineered using the OpenStack cloud architecture, and it meticulously explores advanced scheduling algorithms for virtual machines to enhance platform efficiency. Systematic testing of the platform reveals critical performance metrics; notably, prior to optimization, the CPU utilization of the educational system spikes to 100% with a Time to First Byte (TTFB) reaching indefinite timeouts when concurrent accesses surpass 9, 000, leading to a system shutdown and cessation of service availability. Post-optimization, the platform robustly sustains business accessibility even under similar stress conditions. Furthermore, the empirical usage data of the sports management systems indicate predominant utilization for fulfilling work-related needs (0.796), psychological requirements (0.74), and the pursuit of enhanced operational efficiency (0.732). </p>
</abstract>

The challenge of managing information in collegiate physical education has progressively escalated, thereby amplifying the complexities inherent in the sports management domains at higher education institutions. The advent of artificial intelligence technology heralds a promising avenue for the evolution of sports management frameworks within these settings. This study delineates the development of a specialized cloud platform tailored for the management of collegiate sports, encompassing aspects such as teaching and research management, quality assurance in education, general teaching affairs, practical instruction, and support for auxiliary teaching processes. This platform is engineered using the OpenStack cloud architecture, and it meticulously explores advanced scheduling algorithms for virtual machines to enhance platform efficiency. Systematic testing of the platform reveals critical performance metrics; notably, prior to optimization, the CPU utilization of the educational system spikes to 100% with a Time to First Byte (TTFB) reaching indefinite timeouts when concurrent accesses surpass 9, 000, leading to a system shutdown and cessation of service availability. Post-optimization, the platform robustly sustains business accessibility even under similar stress conditions. Furthermore, the empirical usage data of the sports management systems indicate predominant utilization for fulfilling work-related needs (0.796), psychological requirements (0.74), and the pursuit of enhanced operational efficiency (0.732).

Research on the Innovative Model of Artificial Intelligence Technology Facilitating Sports Management in Colleges and Universities

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The challenge of managing information in collegiate physical education has progressively escalated, thereby amplifying the complexities inherent in the sports...

Research on the Innovative Model of Artificial Intelligence Technology Facilitating Sports Management in Colleges and Universities

Publicado en línea: 09 jul 2024

Páginas: -

Recibido: 13 mar 2024

Aceptado: 02 jun 2024

DOI: https://doi.org/10.2478/amns-2024-1806

Palabras clave
OpenStack cloud framework, Scheduling of virtual machines, Cloud platform, Artificial intelligence technology, University sports management

© 2024 Bingcai Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the Innovative Model of Artificial Intelligence Technology Facilitating Sports Management in Colleges and Universities

Publicado en línea: 09 jul 2024

Páginas: -

Recibido: 13 mar 2024

Aceptado: 02 jun 2024

DOI: https://doi.org/10.2478/amns-2024-1806

Palabras claveOpenStack cloud framework, Scheduling of virtual machines, Cloud platform, Artificial intelligence technology, University sports management

© 2024 Bingcai Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
OpenStack cloud framework, Scheduling of virtual machines, Cloud platform, Artificial intelligence technology, University sports management