5G network education system based on multi-trip scheduling optimization model and artificial intelligence

Abstract

In today’s society, the development of the new ecology of smart education has brought new opportunities and challenges to our country's future education, which all benefit from the rapid development of 5G technology industry. As we all know, multi trip scheduling optimization model is always the focus of distributed computing platform. The goal of distributed platform multi trip scheduling is to find a reasonable task scheduling strategy to minimize the task completion time, which includes transmission time, calculation time and result return time. Most of the existing studies assume that the return time of the results can be ignored, but in fact, the transmission time of the conclusions can not be ignored. Therefore, an updated scheduling model is very important. This paper discusses a new model, namely multi trip scheduling optimization model, which needs algorithm to calculate reasonable values. In view of this, this paper studies the multi trip scheduling optimization model with result collection under two communication modes, and designs an efficient algorithm to solve the model.