Using fog computing (FC) and optimization techniques for tasks migration and resource allocation in the internet of things (IoT)

被引：0
作者：
Arvaneh F. [1 ]
Zarafshan F. [2 ]
Karimi A. [1 ]
机构：
[1] Department of Computer Engineering, Arak Branch, Islamic Azad University, Arak
[2] Department of Computer Engineering, Ashtian Branch, Islamic Azad University, Ashtian
来源：
International Journal of Computers and Applications | 2024年 / 46卷 / 02期
关键词：
cloud computing; fog computing; Iot; resource allocation; tasks migration;
D O I：
10.1080/1206212X.2023.2287257
中图分类号：
学科分类号：
摘要：
The present paper proposes a novel algorithm with the highest accuracy and efficiency for resource allocation in the IoT, considering the fog computing technique. To meet the need for resource allocation, including central processing unit, bandwidth, and main memory, the Genetic Algorithm, Particle Swarm Optimization, Adaptive Weighted Particle Swarm Optimization, Crystal Structure Algorithm, and Simulated Annealing were examined. The obtained results emphasize the better performance of Simulated Annealing compared to the rest. The findings of this paper can benefit optimizing the tasks migration in internet of things. The major innovation of this research lies in the heart of the comparison made between the selected algorithms to see which one conducted the migration tasks with the highest accuracy and remarkable convergence rate. © 2024 Informa UK Limited, trading as Taylor & Francis Group.
引用
收藏
页码：113 / 121
页数：8
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