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A hybrid particle swarm optimization for service identification from business process

机译:用于从业务流程识别服务的混合粒子群优化

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Service identification - as the first step of Service-Oriented Architecture -holds the main emphasis on the modeling process and has a broad influence on the system development. Selecting appropriate service identification method is essential for the prosperity of any service-oriented architecture project. Existing methods for service identification ignore the automation capability while providing human based prescriptive guidelines, which mostly are not applicable at enterprise scales. In this paper, we propose a top down approach to identify automatically services from business process. We use for clustering a hybrid particle swarm optimization algorithm and several design metrics for produce reusable services with proper granularity and acceptable level of cohesion and coupling. The experimental results show that our method HPSOSI (Hybrid Particle Swarm Algorithm for Service Identification) can achieve a high performance in terms of execution time and convergence speed.
机译:服务识别-面向服务的体系结构的第一步-主要强调建模过程,并且对系统开发产生广泛的影响。选择合适的服务标识方法对于任何面向服务的体系结构项目的繁荣至关重要。现有的服务识别方法在提供基于人的说明性准则时会忽略自动化功能,而这在企业范围内大多不适用。在本文中,我们提出了一种自上而下的方法来从业务流程中自动识别服务。我们将一种混合粒子群优化算法和一些设计指标用于聚类,以产生具有适当粒度和可接受的内聚和耦合水平的可重用服务。实验结果表明,我们的方法HPSOSI(用于服务识别的混合粒子群算法)可以在执行时间和收敛速度方面达到较高的性能。

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