Abstract: In cloud computing environments,as the number and types of containers continue to increase,resource management and scheduling complexity are increased.How to effectively schedule containers and optimize resource utilization and cluster perfor-mance has become an important research topic.The existing container cluster scheduling strategies do not fully consider the diverseneeds of containers,lack flexibility,and are difficult to customize scheduling for containers in different scenarios.This can easily lead to problems such as low cluster resource utilization and imbalanced cluster resource load.In order to meet the diverse needs of containers and improve the load balancing of cluster resources,this paper proposes a customized container scheduling strategy based on GMM(Gaussian Mixture Model).Firstly,classify according to the resources and attribute requirements of the container,and divide it into different types.Secondly,for each type of container,different independent weights are calculated and assigned separately,and the containers are scheduled to appropriate nodes according to their types in turn,thereby achieving customized scheduling.In this way,the diverse needs of containers are met,so that different types of containers can get the optimal resource allocation according to their specific needs,avoiding resource competition and conflicts,thereby improving the overall utilization and load balancing of cluster resources.Experimental results show that compared with Kubernetes Scheduler,this scheduling strategy has shown superior performance in various container scheduling scenarios,with the maximum resource utilization diffe-rence between cluster nodes reduced by 17.1%,the container scheduling success rate increased by 19%,and the cluster node load balancing increased by 57.51%.

Key words: Cloud computing, Container scheduling, Diversification, Customization, Load balancing