基于聚类和Skyline计算的云计算服务选择

Service Selection for Cloud Computing Environment Based on Skyline Computing and Clustering

针对云计算环境中存在着大量功能相同或类似而服务质量不同的服务,而实现对这些服务选取的方法往往具有效率低和实时性差的缺点,为此,提出了一种基于聚类和Skyline计算的云计算服务选择方法;首先,对各抽象服务类采用相似度矩阵进行分类,选取其中与用户服务请求最匹配的分类作为候选分类;然后,通过Skyline计算剔除各候选分类中的冗余服务,保留支配服务作为候选服务;最后,通过最大化效用函数来选取候选服务构成组合服务;仿真实验表明文中方法能高效地实现云计算环境下的服务选取,且与其它方法比较,与用户服务请求需求具有较高的匹配度,服务选择精确度达到100%,同时算法的时间复杂度较低,具有较大的优越性。

Aiming at the service selection method in cloud computing which has a lot of similar or same functions but different quality service environment has the defects of low efficiency and real--time performance, therefore, a service selection method based on clustering and skyline computing was proposed. Firstly, the fuzzy clustering method was used to classify the abstract service class, the class with the best match ability with the user service request was defined as the candidate class, then the skyline computing was used to get the dominated candidate service, finally, the compound service was obtained by maximizing the utility function. The experiment shows the method in this paper can realize service selection in cloud computing, and compared with the other methods, it has the larger matching ability with the user request constraint with the lower algorism complexity, and the service selection accuracy is as high as 100%. Therefore it is proved has big priority.