Differential Evolution Cloud Computing Scheduling Strategy Based on Dynamic Adjustment

Abstract

AbstractThis paper presents an improved differential evolution algorithm(CDEI) to solve the problem of resource scheduling and load balancing in clofud computing environment. Firstly, based on the basic differential evolution algorithm, the chaotic strategy is introduced and the individual replacement is implemented at the right time to enhance the diversity of the population; furthermore, the scaling factor and crossover probability are dynamically adjusted in the iteration of the algorithm, and the strategy of early high to low is adopted to overcome the prematurity of the algorithm; finally, the array representation is used in the coding of cloud computing scheduling. The experimental results show that the improved algorithm has the advantages of fast convergence, high precision and low consumption.