<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>Integrating Civic Education into computer network technology courses can make the professional content more profound. This paper proposes an optimization scheme to improve the teaching effect of the course with an ant colony algorithm, tests the optimization effect of the ant colony scheduling algorithm on the computer network technology course through the index of assignment completion time, and compares the completion time of the same assignment content using four schedulers, ACOScheduler, FIFOScheduler, CapacityScheduler, and FairScheduler, respectively, in the same The results show that the completion time of the same job content in the same environment using ACOScheduler, FIFOScheduler, CapacityScheduler, and FairScheduler. The results show that the task completion time of ACOSchduler is 9.8% lower than that of FairScheduler and 11.4% lower than that of CapacityShcduler at a task size of 500MB, thus optimizing the effectiveness of teaching computer network technology courses. The performance optimization effect of the ACOS scheduling algorithm on the course teaching reform, the achievement of all the target functions to improve the efficiency of task scheduling, more efficient data analysis tasks, and the achievement of the requirements of the expected teaching reform of the subject.</p>
</abstract>

Integrating Civic Education into computer network technology courses can make the professional content more profound. This paper proposes an optimization scheme to improve the teaching effect of the course with an ant colony algorithm, tests the optimization effect of the ant colony scheduling algorithm on the computer network technology course through the index of assignment completion time, and compares the completion time of the same assignment content using four schedulers, ACOScheduler, FIFOScheduler, CapacityScheduler, and FairScheduler, respectively, in the same The results show that the completion time of the same job content in the same environment using ACOScheduler, FIFOScheduler, CapacityScheduler, and FairScheduler. The results show that the task completion time of ACOSchduler is 9.8% lower than that of FairScheduler and 11.4% lower than that of CapacityShcduler at a task size of 500MB, thus optimizing the effectiveness of teaching computer network technology courses. The performance optimization effect of the ACOS scheduling algorithm on the course teaching reform, the achievement of all the target functions to improve the efficiency of task scheduling, more efficient data analysis tasks, and the achievement of the requirements of the expected teaching reform of the subject.

Research on the reform and practice of thinking and teaching of computer network technology course based on ant colony algorithm

Applied Mathematics and Nonlinear Sciences

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

Integrating Civic Education into computer network technology courses can make the professional content more profound. This paper proposes an optimization...

Research on the reform and practice of thinking and teaching of computer network technology course based on ant colony algorithm

Data publikacji: 01 sie 2023

Zakres stron: -

Otrzymano: 12 paź 2022

Przyjęty: 09 lut 2023

DOI: https://doi.org/10.2478/amns.2023.2.00122

Słowa kluczowe
Big data, Ant colony algorithm, Computer network technology course, Civics teaching

© 2023 Weigang Liu, published by Sciendo

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

Research on the reform and practice of thinking and teaching of computer network technology course based on ant colony algorithm

Data publikacji: 01 sie 2023

Zakres stron: -

Otrzymano: 12 paź 2022

Przyjęty: 09 lut 2023

DOI: https://doi.org/10.2478/amns.2023.2.00122

Słowa kluczoweBig data, Ant colony algorithm, Computer network technology course, Civics teaching

© 2023 Weigang Liu, published by Sciendo

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

Słowa kluczowe
Big data, Ant colony algorithm, Computer network technology course, Civics teaching