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A Partial Selection Methodology for Efficient QoS-Aware Service Composition

机译:高效QoS感知服务组合的部分选择方法

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As web service has become a popular way for engineering software on the Internet, quality of service (QoS) which describes non-functional characteristics of web services is often employed in service composition. Since QoS is an aggregated concept consisting of several attributes, service composition on enormous candidate sets is a challenging multi-objective optimization problem. In this paper, we study the problem from a general Pareto optimal angle, seeking to reduce search space in service composition. Pareto set model for QoS-aware service composition is introduced, and its relationship with the widely used utility function model is theoretically studied, which proves the applicability of our model. QoS attributes are systematically studied according to their different types of aggregation patterns in service composition, and QoS-based dominance relationships between candidates and between workflows are defined. Taking advantage of pruning candidates by dominance relationships and constraint validations at candidate level, a service composition algorithm using partial selection techniques is proposed. Furthermore, a parallel approach is designed, which is able to significantly reduce search space and achieve great performance gains. A careful analysis of the optimality of our approach is provided, and its efficacy is further validated by both simulation experiments and real-world data based evaluations.
机译:由于Web服务已成为Internet上工程软件的流行方式,因此在服务组合中通常采用描述Web服务非功能特性的服务质量(QoS)。由于QoS是一个由几个属性组成的聚合概念,因此在大量候选集上的服务组合是一个充满挑战的多目标优化问题。本文从广义帕累托最优角度研究问题,力图减少服务组合中的搜索空间。介绍了用于QoS感知服务组合的Pareto集模型,并从理论上研究了其与广泛使用的效用函数模型的关系,证明了该模型的适用性。根据服务组合中不同类型的聚合模式,系统地研究了QoS属性,并定义了候选之间以及工作流之间基于QoS的优势关系。利用优势关系和候选者级别的约束验证对候选者进行修剪的优点,提出了一种使用部分选择技术的服务组合算法。此外,设计了一种并行方法,该方法能够显着减少搜索空间并获得巨大的性能提升。提供了对我们方法最优性的仔细分析,并通过模拟实验和基于实际数据的评估进一步验证了其有效性。

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