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Aiming at conquering the defects of long task scheduling time and unbalance of system load in the existing task scheduling method, a task scheduling method based on dependence task and Sarsa(λ) is proposed. Firstly, the scheduling model is defined and minimizing the finishing time of scheduling strategy as the scheduling goal. The task scheduling model is modeled as the Markov decision process (MDP), then the state action value is renewed by combing MDP and Sarsa algorithm. In order to accelerate the convergence rate, the eligibility is added to the updating for state action value, and the updating for eligibility is given. Finally, the task scheduling algorithm in cloud computing by combing dependence task DAG graph and Sarsa(λ) is specified. The experiment is operated in the Cloudsim environment, the result shows the method in this paper can realize dependent task cluster scheduling, and compared with the other methods, it has the less task scheduling time and higher load balance, therefore, it is a feasible scheduling method suitable for cloud environment.