Study on the Resource Allocation Optimization in Cloud Computing Based on the Hybrid Optimization Algorithm

Abstract

The methods of solving resource allocation are mainly heuristic algorithms which could not solve resource allocation problems in cloud computing. The hybrid optimization algorithm is studied to solve the problem. There are many different hybrid optimization algorithms. Our research hopes to find a simple and effective method. We select a combination optimization algorithm of the genetic and ant colony algorithms. In the early phase of this algorithm, with the help of the wide range search capabilities of the genetic algorithm, it finds a better solution; in the later stage of this algorithm, with the help of positive feedback and efficiency of the ant colony algorithm, it finds the optimal solution. In addition, the two algorithms convergence conditions and the way of how to make the better solution of the genetic algorithm translate into the initial pheromone distribution provisions of the ant colony algorithm are set up. At last, the algorithm was realized with a simulation environment, and a specific example was made by comparative analysis to verify the correctness and effectiveness of the algorithm