Cloud computing load balancing based on improved genetic algorithm

In the cloud computing environment, when most users request services, how to quickly and reasonably allocate a large number of tasks to a single virtual resource node and achieve parallelism is one of the research topics of current researchers. The key to this method in load balancing technology is load programming, whose quality directly affects the performance of the equalisation system. Therefore, this paper starts with distributed cloud computing technology and virtualisation technology, reveals the concept and method of load balancing implementation, and proposes an improved genetic load balancing algorithm. Traditional genetic algorithms can be used as meta-heuristic algorithms with slow convergence problems. We used the Cloudsim open source cloud simulation platform for simulation. The results show that compared with the traditional genetic algorithm, the improved genetic algorithm can better adapt to the load balancing requirements in the cloud computing environment and improve the balance and efficiency of resource utilisation.