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Optimization of Innovation and Entrepreneurship Education and Training System in Colleges and Universities Based on OpenStack Cloud Computing.

Authors :
Xu, Chunyan
Song, Cai
Source :
Scientific Programming. 8/30/2022, p1-12. 12p.
Publication Year :
2022

Abstract

With economic globalization and rapid development of science and technology, many colleges and universities pay more and more attention to the cultivation of students' innovative thinking and creativity, and innovation and entrepreneurship education has also become an important part of the education system. Due to the current unevenness of teachers in innovation and entrepreneurship education in colleges and universities, high training cost, and lack of strong atmosphere, this paper optimizes the innovation and entrepreneurship education and training system in colleges and universities through OpenStack cloud computing. This paper optimizes the cloud computing platform according to the OpenStack virtual machine and the multiobjective ant colony improvement algorithm and then designs the innovation and entrepreneurship education and training system. The multiobjective ant colony improvement algorithm uses the way ants find food to find the best information resource route from the traces left by the information trend in the cloud platform. In order to test the effectiveness of these methods, this paper uses the simulation method to test. The results show that, sometimes, the load utilization rate of the innovation and entrepreneurship education and training system in colleges and universities exceeds 80%, which is in line with the expected settings. Through the OpenStack cloud computing platform, it can provide a good innovation and entrepreneurship training environment for more users at low cost and low risk and promote the development of innovation and entrepreneurship education. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10589244
Database :
Academic Search Index
Journal :
Scientific Programming
Publication Type :
Academic Journal
Accession number :
158816321
Full Text :
https://doi.org/10.1155/2022/2868499