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A QoS-Aware Service Optimization Method Based on History Records and Clustering

机译:基于历史记录和群集的QoS感知服务优化方法

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The number of alternative Web services that provide the same functionality but differ in non-functional characteristics, i.e., Quality of Service (QoS) parameters is more and more larger, and the service providers could not always deliver their """"promised"""" quality. In view of this challenge, we propose a QoS-aware service optimization method based on history records and clustering, named QHRC. In this method, we take advantage of the history records of services' past performance quality rather than using the tentative QoS values provided by the service providers. And an adaptive hierarchical fuzzy clustering algorithm named H2D-SC algorithm is adopted to cluster the QoS history records for each Web service, then using the centroids of the sub clusters to generate QoS history-record based composition plans. Our method aims at ranking the service composition plans by the corresponding QoS history-record based composition plans to select a most qualified service composition plan. At last, we assess the efficiency of the proposed method with an example and experiments.
机译:提供相同功能但在非功能性特征中的替代Web服务的数量,即服务质量(QoS)参数越来越大,并且服务提供商不能总是提供他们的&#x0022 ;""承诺""""质量。鉴于这一挑战,我们提出了一种基于历史记录和群集的QoS感知服务优化方法,命名为QHRC。在这种方法中,我们利用服务过去性能质量的历史记录,而不是使用服务提供商提供的暂定QoS值。并且采用名为H2D-SC算法的自适应分层模糊群集算法为每个Web服务群体群体历史记录,然后使用子集群的质心来生成基于QoS历史记录的组合计划。我们的方法旨在通过基于QoS历史记录的组合计划进行排名,以选择最合格的服务成分计划。最后,我们通过示例和实验评估所提出的方法的效率。

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