Abstract: Based on the coral reef optimization algorithm, we proposed a genetic coral reef optimization algorithm by introducing crossover and mutation operators in genetic algorithm into each evolution process of population. The improved genetic coral reef optimization algorithm was applied to load balancing. The  algorithm effectively solves the problem of premature convergence and improves the optimization performance of the algorithm. Comparing swarm intelligence algorithms such as classical genetic algorithm and coral reef optimization algorithm, simulation results on CloudSim show that the genetic coral reef optimization algorithm achieves satisfactory results in optimizing load balancing strategy, thus improving the utilization rate of energy consumption and balancing the control strategy.

Key words: cloud computing, load balancing, genetic algorithm, coral reef optimization algorithm