A Multi-objective Discrete PSO Algorithm for Simulation Components Deployment in the Cloud and Edge Environment

Abstract

The booming cloud computing, together with edge computing, lays the computing resource foundation for larger and more granular simulation. To achieve better execution of the simulation in cloud and edge environments, it is necessary to assign simulation components to cloud computing centers and edge computing nodes appropriately. This is an optimization problem and a particle swarm optimization(PSO) algorithm is proposed for this purpose. However, deployment problems are a kind of discrete optimization problem and PSO algorithm was originally designed to solve continuous optimization problems, thus, various discretization methods had been proposed to modify original PSO algorithm to handle discrete problems. Unsatisfactorily, many discrete PSO algorithms suffer from random movements of particles due to improper use of the guidance information obtained from the global best particle and personal best particle. To counter this challenge, we proposed a selection-based discrete PSO algorithm(SPSO) and conducted simulation experiments on MATLAB platform. The results showed that SPSO got better performance in simulation components allocation problems compared with NSGA-II and other pure discrete PSO algorithms.