Intelligent Method for Cloud Task Scheduling Based on Particle Swarm Optimization Algorithm

The core idea of cloud computing is managing and scheduling uniformly computing resources that are connected by a network to provide user services according to the needs. One of the important issues in this environment is related to task scheduling. The scheduler should do the scheduling process efficiently in order to utilize the available resources. In this paper, a particle swarm optimization algorithm for cloud task scheduling has been proposed. Particle swarm optimization algorithm is a computational method that optimizes a solution to problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. The main goal of the proposed algorithm is minimizing the makespan of a given tasks set. The proposed algorithm has been compared with ant colony optimization and random algorithms using CloudSim toolkit package. Experimental results showed that the proposed algorithm outperformed ant colony optimization and random algorithms.