Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

December 18, 2023


Pages


DOI

Article

Research on Teaching Resource Management in Colleges and Universities Based on Multiple Data Chain Networks

Check for updates


Authors

Kunpeng Wang Affiliation:
Office of Academic Affairs, Changzhou Institute of Technology, Changzhou, Jiangsu, 213022, China.


Abstract

In this paper, we first take the datalink network as the entry point and construct a university teaching resource management model based on a multivariate datalink network. A Link-22 data chain time synchronization algorithm with KF-RTPT is proposed to address the actual existence and unavoidable time deviation based on accuracy and timestamp acquisition errors. Meanwhile, a time slot allocation and optimization algorithm designed to maximize message transmission benefits is being developed to optimize the allocation of node time slot requirements. Finally, the constructed teaching resource management model is empirically analyzed from three perspectives: error optimization, dynamic time slot allocation, and model application effect. According to the findings, the KF-RTPT algorithm increases motion error efficiency by 3.83 in low-speed motion states and 8.16 in high-speed motion states when compared to the conventional RTT method. This effectively eliminates motion error and boosts the effectiveness of teaching and managing resources in colleges and universities.


Keywords

Data chain network, Time deviation, KF-RTPT, Time slot allocation and optimization, Teaching resource management, 97C70


Citation

Wang, K. (2023). Research on teaching resource management in colleges and universities based on multiple data chain networks. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01520

Published by: Engineering Journals

Engineering Journals Logo