Genetic Ant Colony Algorithm Improves Resource Scheduling in Cloud Computing

Abstract

When a large number of users request cloud computing resource services, rational organization of resources and task scheduling is one of the key technologies of cloud computing. Aiming at the problems of low efficiency and slow convergence speed of existing cloud computing resource scheduling algorithms, combined with the characteristics of global search ability of genetic algorithm and positive feedback convergence of ant colony algorithm, a resource scheduling algorithm is proposed. The initial pheromone distribution is generated by the genetic operator, and the exact solution is obtained by the bidirectional convergence ant colony operator. The experimental results show that the proposed algorithm is superior in solving accuracy and convergence speed, and it is an effective cloud computing resource scheduling algorithm.