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Task scheduling is a necessary prerequisite for performance optimization and resource management in the cloud computing system. Focusing on accurate scaled cloud computing environment and efficient task scheduling under resource constraints problems, we introduce fine-grained cloud computing system model and optimization task scheduling scheme in this paper. The system model is comprised of clearly defined separate submodels including task schedule submodel, task execute submodel and task transmission submodel, so that they can be accurately analyzed in the order of processing of user requests. Moreover the submodels are scalable enough to capture the flexibility of the cloud computing paradigm. By analyzing the submodels, where results are repeated to obtain sufficient accuracy, we design a novel task scheduling scheme based on reinforcement learning and queuing theory to …