Abstract: Under the cloud computing environment, it has become a significant problem to decrease the power consumption while the makespan is shortened in the process of scheduling resource. Thus, this paper made span and power consumption as the optimization objectives and established power-aware resource scheduling model, then improved the Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ) by adopting special initialization and the learning algorithm, to solve the problem of power-aware scheduling. Consequently, the simulation results prove that the proposed scheduling algorithm not only shortens the makespan, but also decreases the power consumption effectively.

Key words: cloud computing, resource scheduling, power consumption, bi-objective optimization, Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ)

摘要： 在云计算环境下，如何在有效地进行资源调度，缩短任务执行时间的同时，降低能耗，已经成为一个重要问题。对此，以任务执行时间与能耗作为优化目标，建立了一个节能调度模型，并通过采用特殊的种群初始化方法以及引入学习机制等方法对非支配排序遗传算法(NSGA-Ⅱ)进行改进，将其应用于云计算的节能调度问题。最后通过算例测试，验证了所提算法能够在减少任务执行时间的同时，有效降低能耗。

关键词: 云计算, 资源调度, 能耗, 双目标优化, 非支配排序遗传算法