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Towards an efficient and a more accurate web service selection using MCDM methods

机译:使用MCDM方法实现高效,更准确的Web服务选择

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Nowadays, due to the fast growth of the number of web services with the same functionalities, the selection of the best services becomes a tricky task. Therefore, to provide a more powerful selection tool, web services are now additionally distinguished with respect to their non-functional aspects, especially to Quality of Service (QoS) requirements. Indeed, using QoS perspective in web service selection can help to promote the best candidate web services among those holding the same functional requirements. Hitherto, various QoS based web service selection approaches have been explored in the literature. However, two main challenging and conflicting issues are still demanding a specific attention, namely how accurate is the selection and what is the cost of such a process? In this paper, we target Multi Criteria Decision Making (MCDM) methods to select web services. Within this context, we propose a hybrid method to select the optimal web services based on MCDM. First of all, we use the Skyline method to reduce the research space by removing the dominated web services. Then, the BWM (Best Worst Method) is applied to normalize the weights associated with the QoS parameters according to the user request requirements. To rank the non-dominated web services with respect to the weights normalization, we explore the use of four different MCDM approaches that enjoy an affordable complexity, which are: VIKOR, SAW, TOPSIS and COPRAS. For the sake of a comparison, each method is first tested separately in order to assess its ability to select the optimal elements. Then, in order to provide the best compromise between the different ranking methods, we apply the Borda voting method to determine the compromise solution. Hence, we are able to measure the accuracy of each technique relatively to the Borda solution by applying a similarity function. The implementation and the simulation of the different methods have permitted to assess their performances in terms of time execution and accuracy. The results show clearly that MCDM ranking methods are more likely to diverge in selecting the best elements when the number of web services is increased. This finding argues for the pertinence of computing the Borda solution in the context of MCDM based web service selection. (C) 2017 Elsevier B.V. All rights reserved.
机译:如今,由于功能相同的Web服务数量的快速增长,选择最佳服务已成为一项棘手的任务。因此,为了提供更强大的选择工具,现在在服务的非功能性方面,尤其是在服务质量(QoS)要求方面,进一步区分了Web服务。确实,在Web服务选择中使用QoS观点可以帮助在具有相同功能要求的服务中提升最佳候选Web服务。迄今为止,文献中已经探索了各种基于QoS的Web服务选择方法。但是,仍然需要特别注意两个主要的挑战性和冲突性问题,即选择的准确性如何以及该过程的成本是多少?在本文中,我们针对多准则决策(MCDM)方法来选择Web服务。在此背景下,我们提出了一种基于MCDM的混合方法来选择最佳Web服务。首先,我们使用Skyline方法通过删除主导的Web服务来减少研究空间。然后,根据用户请求要求,应用BWM(最佳最差方法)对与QoS参数关联的权重进行归一化。为了根据权重归一化对非主导的Web服务进行排名,我们探索了使用四种可承受的复杂性的MCDM方法:VIKOR,SAW,TOPSIS和COPRAS。为了进行比较,首先分别测试每种方法,以评估其选择最佳元素的能力。然后,为了在不同排名方法之间提供最佳折衷,我们采用Borda投票方法来确定折衷解决方案。因此,我们能够通过应用相似性函数来测量每种技术相对于Borda解决方案的准确性。不同方法的实现和仿真已允许在时间执行和准确性方面评估其性能。结果清楚地表明,随着Web服务数量的增加,MCDM排名方法在选择最佳元素方面更有可能发生分歧。这一发现证明了在基于MCDM的Web服务选择的背景下计算Borda解决方案的相关性。 (C)2017 Elsevier B.V.保留所有权利。

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