An intelligent management and decision model of operational research for edge computing aided planning

• Published in: Alexandria engineering journal Vol. 109; pp. 603 - 609
• Main Author: Zhang, Yuanshou
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2024; Elsevier
• Subjects: Edge Algorithm; Intelligent Decision-making Model; Mobile Edge Computing Server; Task Offloading; Intelligent Decision-making Model; Task Offloading; Edge Algorithm; Mobile Edge Computing Server
• ISSN: 1110-0168; 2090-2670
• DOI: 10.1016/j.aej.2024.09.072

With the development of “Internet plus” and the deep integration of information and network based technology and network technology, Industry 4.0 has become a hot topic. Industrial production is faced with a large number of tasks, complex and changeable demands, and difficult to predict. In order to solve a series of objective problems such as task delay in actual production, this paper proposed a method based on edge computing (EC) to reduce the delay to meet the real-time requirements of industrial production. However, due to the limitation of its computing power and storage capacity, it is difficult to adapt to large-scale data decision-making. In terms of the lag rate of the algorithm in the experiment of the intelligent decision model, when the number of tasks of EC algorithm was 15 and 6, the lag rate was the highest and the lowest, and its values were 16 % and 2 % respectively. Therefore, it can be seen that EC algorithm can play a good role in the intelligent management and decision-making model of operational research.