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PSO-inspired BIRCH and Improved Bipartite Graph for Automatic Web Service Composition

机译:PSO激发的桦木和改进的自动Web服务组成的二分拉图

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摘要

Web services are published by the service providers through the internet as independent software components by fulfilling the requirements of the customer requests. As the customer requests are not always satisfied by a single service, the methods of services composition were evolved in which a chain of services are composed together. However the longer search time for the discovery of composed services is a challenging problem causing the customer to wait long time especially while using larger web service set. In this paper, an efficient automatic web service composition approach is proposed to improve the performance by introducing domain-ontology-based PSO-inspired Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) clustering and Improved Bipartite graph in the pre-processing and service discovery & ranking phases respectively. Domain-ontology-based PSO-inspired BIRCH incrementally and dynamically clusters the web services in hierarchical manner with optimizing the clustering results to reduce the processing time. The approach improves clustering quality by additional scans and thus creating sophisticated environment for service matchmaking. In discovery phase, the Improved Bipartite graph produces maximal bicliques by pruning the non-maximal bicliques in the search space without restricting the inputs and reduced computations for elimination. Thus the best service clusters is discovered and ranked which ensures the selection of best composition plan in the planning, verification & execution phase. Experimental results performed in terms of accuracy, runtime, recall and precision, shows that the proposed framework improves the efficiency of web service composition.
机译:通过满足客户请求的要求,服务提供商通过互联网作为独立软件组件发布Web服务。由于客户请求并不总是通过单一服务满足,因此进化了服务组合方法,其中一系列服务组合在一起。然而,搜索组成的服务的搜索时间越长是一个具有挑战性的问题,导致客户等待很长一段时间,特别是在使用较大的Web服务集时。在本文中,提出了一种高效的自动Web服务组合方法,通过在预处理和服务发现中引入基于域 - 本体的PSO鼓励的平衡迭代还原和聚类来提高性能。和排名阶段。基于域的PSO-Inspired Birch逐步地以分层方式动态地将Web服务群化,并优化聚类结果以减少处理时间。该方法通过额外的扫描提高了聚类质量,从而创建了用于服务匹配的复杂环境。在发现阶段,改进的二分曲线图通过在搜索空间中修剪非最大双层的非最大双板而不限制输入和减少的消除计算来产生最大双层。因此,发现和排名最佳的服务群集,确保在规划,验证和执行阶段中选择最佳组合计划。在准确性,运行时,召回和精度方面进行的实验结果表明,所提出的框架提高了Web服务组合的效率。

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