中文摘要：

多QoS约束下的工作流调度是网格计算中难以求解的问题．在深入剖析该问题难解性基础上，采用克隆选择算法求解该问题．首先通过增加网格服务的唯一标识，简化工作流调度的编码方式．其次，提出QoS偏好的概念，将调度问题的目标函数转换为适应值函数．该算法具有QoS属性的可扩展性．最后通过大量实验，优化算法参数，与基于遗传算法、蚁群算法的调度算法对比，克隆选择算法求解效率较优．在扩展情况下，与单一QoS约束下的时间、费用贪婪算法对比，克隆选择算法能进行最优调度．

英文摘要：

Workflow scheduling with muhi-QoS constraints is hard to be solved under the grid computing environment. A clonal selection algorithm, named EvoWF, is proposed to solve workflow scheduling problem based on deep analysis on the difficulty of this problem. The encoding of working scheduling is simplified by adding the grid service identification. The concept of QoS preference is proposed, which converts object function of workflow scheduling to fitness function, and QoS attributes can be extended. Compared to genetic algorithm and ant colony optimization, EvoWF is more efficient. In extension, EvoWF gets the same optimum scheduling results compared with the single-QoS constraint greed time or cost algorithm. Moreover, the effect of parameters is analyzed by experiments.