Research on cloud computing resource scheduling strategy based on genetic ant colony fusion algorithm

Abstract

In this paper, ant colony algorithm and genetic algorithm are combined to improve the stability and efficiency of cloud computing resource scheduling. The strategy of this algorithm is to use the local optimal solution of genetic algorithm as the initial pheromone of ant colony algorithm, and introduce load balancing adjustment factor and transfer probability into ant colony algorithm. The experimental results show that the genetic ant colony fusion algorithm in this paper has better advantages in the number of iterations, time cost, power cost and load balancing, and achieves the goal of uniform distribution of cloud computing resources.