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Research on intelligent scheduling algorithm of high altitude platform system for wide area internet of things.

Authors :
Wu, Zhou
Guan, Mingxiang
Liu, Ming
Xia, Linzhong
Lv, Changwei
Cao, Xuemei
Chen, Hanying
Source :
Wireless Networks (10220038). Jul2024, Vol. 30 Issue 5, p4017-4023. 7p.
Publication Year :
2024

Abstract

Internet of things technology can not only improve people's lives, but also bring great changes and innovations to the industry and promote the rapid development of economy. The future communication system will be a system of everything connected with IoT. There will be various types of user equipment in the system. The standards adopted by different types of equipment are different, and the required business levels are also different. This will bring great challenges to the resource allocation of the system. Artificial intelligence algorithms provide technical support for future intelligent wireless systems. The system can select appropriate artificial intelligence algorithms according to different application scenarios and establish more accurate mathematical models to serve the network. According to the business priority analysis of user equipment under the wide area Internet of things, considering the user scheduling as the constraint condition, a high-altitude platform user equipment scheduling model based on artificial intelligence k-means algorithm under the user scheduling constraint condition is established. Based on the user equipment scheduling model of high-altitude platform based on artificial intelligence k-means algorithm, a two-stage K-means improved algorithm is proposed to cluster the user equipment of wide area Internet of things, which is divided into preprocessing training stage and K-means algorithm clustering stage. The initial center value is not randomly selected. In the preprocessing training stage, the scheduling priority of each user is obtained according to the channel environment and packet length of the user equipment. The first k user equipment with the same scheduling priority is used as the initial clustering points to complete the preprocessing training. Then, K-means algorithm is used to cluster the new user equipment to be scheduled until convergence. The intelligent scheduling of user equipment under the wide area Internet of things is realized. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10220038
Volume :
30
Issue :
5
Database :
Academic Search Index
Journal :
Wireless Networks (10220038)
Publication Type :
Academic Journal
Accession number :
178231160
Full Text :
https://doi.org/10.1007/s11276-021-02842-5