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Particle Swarm Optimization with Skyline Operator for Fast Cloud-based Web Service Composition

机译:使用Skyline运算符进行粒子群优化以实现基于云的快速Web服务组合

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Quality of Services play an increasingly important role during the procedure of Cloud-based web service composition for seamless and dynamic integration of business applications. However, as Cloud-based web services (CWSs) proliferate, it becomes difficult to facilitate service composition quickly in Cloud computing environment. In this paper, based on the notion of Skyline, we propose a fast CWS composition approach. This approach adopts Skyline operator to prune redundant CWS candidates and then employs Particle Swarm Optimization to select CWS from amount of candidates for composing single service into a more powerful composite service. Based on a real dataset, we conduct an experiment to evaluate our proposed approach. Experimental results show that our proposed approach is effective and efficient for CWS composition.
机译:在基于云的Web服务组合过程中,服务质量在业务应用程序的无缝和动态集成中起着越来越重要的作用。但是,随着基于云的Web服务(CWS)的激增,在云计算环境中快速促进服务组合变得困难。在本文中,基于Skyline的概念,我们提出了一种快速的CWS组合方法。该方法采用Skyline运算符来修剪冗余CWS候选,然后使用粒子群优化从候选数量中选择CWS,以将单个服务组合为功能更强大的组合服务。基于真实的数据集,我们进行了一项实验来评估我们提出的方法。实验结果表明,我们提出的方法对于CWS组合是有效的。

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