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

In the traditional administrative management mode of higher education institutions, different departments work separately, and it is difficult to realize the sharing of information. This paper follows the hierarchical design of J2EE multilayer architecture to build an administrative management platform for colleges and universities. Through cloud computing technology college management information through Hibernate mapping to the object table to achieve data storage and sharing. Simulated annealing algorithms and genetic algorithms are introduced into the system to realize the optimal scheduling of administrative tasks and promote the overall collaborative efficiency of the task process. Finally, the workflow analysis is carried out on the practical cases of administrative management in colleges and universities, and the optimal scheduling of administrative tasks <italic>t</italic>1 ~ <italic>t</italic>9 in colleges and universities is completed. The results show that the platform 400Vuser under the integrated response time of 2.833 seconds less than the expected 3 seconds, the maximum number of concurrency in the maximum response time constraints can reach 4500 or so, to meet the performance requirements of university administrative management. And task <italic>t</italic>1 ~ <italic>t</italic>9 completes the optimal scheduling in the experiment, saving a total of 2 resource types. This system is of great practical significance in improving the efficiency of administrative offices in universities, reducing human errors and saving labor costs.
</abstract>

In the traditional administrative management mode of higher education institutions, different departments work separately, and it is difficult to realize the sharing of information. This paper follows the hierarchical design of J2EE multilayer architecture to build an administrative management platform for colleges and universities. Through cloud computing technology college management information through Hibernate mapping to the object table to achieve data storage and sharing. Simulated annealing algorithms and genetic algorithms are introduced into the system to realize the optimal scheduling of administrative tasks and promote the overall collaborative efficiency of the task process. Finally, the workflow analysis is carried out on the practical cases of administrative management in colleges and universities, and the optimal scheduling of administrative tasks t1 ~ t9 in colleges and universities is completed. The results show that the platform 400Vuser under the integrated response time of 2.833 seconds less than the expected 3 seconds, the maximum number of concurrency in the maximum response time constraints can reach 4500 or so, to meet the performance requirements of university administrative management. And task t1 ~ t9 completes the optimal scheduling in the experiment, saving a total of 2 resource types. This system is of great practical significance in improving the efficiency of administrative offices in universities, reducing human errors and saving labor costs.

Innovation of Administrative Management System of Universities Based on Cloud Computing

Applied Mathematics and Nonlinear Sciences

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

In the traditional administrative management mode of higher education institutions, different departments work separately, and it is difficult to realize the...

Innovation of Administrative Management System of Universities Based on Cloud Computing

Online veröffentlicht: 16. Dez. 2023

Seitenbereich: -

Eingereicht: 02. Feb. 2023

Akzeptiert: 26. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01495

Schlüsselwörter
Administrative management platform, Cloud computing technology, Simulated annealing algorithm, Genetic algorithm, Optimal scheduling

© 2023 Li Wang, published by Sciendo

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

Innovation of Administrative Management System of Universities Based on Cloud Computing

Online veröffentlicht: 16. Dez. 2023

Seitenbereich: -

Eingereicht: 02. Feb. 2023

Akzeptiert: 26. Juni 2023

DOI: https://doi.org/10.2478/amns.2023.2.01495

SchlüsselwörterAdministrative management platform, Cloud computing technology, Simulated annealing algorithm, Genetic algorithm, Optimal scheduling

© 2023 Li Wang, published by Sciendo

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

Schlüsselwörter
Administrative management platform, Cloud computing technology, Simulated annealing algorithm, Genetic algorithm, Optimal scheduling