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

Abstract

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.