一种关联感知的组合服务重选取方法

已有的组合服务重选取方法大都假定任务之间互相独立,然而在实际场景中,由于基本服务间存在着Qo S关联关系,使得某些任务之间也存在着关联关系,从而导致这些已有的方法难以获取最佳的调整方案.针对该问题,通过扩展OWL-S,给出了一个支持服务间关联关系的Qo S模型.基于该模型,给出了一个支持任务间关联关系的重选取算法,该算法将具有关联关系的任务作为一个任务单元,以关联服务作为任务单元的备选服务进行重选取.实验结果表明,与按照任务间独立的方式进行重选取相比,该方法能有效提高重新选取出的组合服务质量.

Composite Service Reselection Method of Correlation-Aware

Most of the existing researches for composite service reselection method are based on the assumption that the tasks involved are independent. However， in practical scenarios， the QoS of some candidate services have correlations with other services， which leads to the reselected results not to be the optimal one in the real executing environment for these existing reselection methods. To solve this problem， a QoS model supporting the correlations between services was given by extending the OWL-S framework. Based on the proposed model， a composite service reselection method considering the correlations among tasks was provided， in which the correlated tasks were regarded as a task unit and the correlated services of each task unit were regarded as its candidate service set. Experimental results showed that compared with the reselection methods considering the tasks independent， the proposed approach could effectively improve the quality of composite service reselected.