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首页> 外文期刊>Knowledge and Data Engineering, IEEE Transactions on >Efficient Service Skyline Computation for Composite Service Selection
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Efficient Service Skyline Computation for Composite Service Selection

机译：组合服务选择的高效服务天际线计算

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摘要

Service composition is emerging as an effective vehicle for integrating existing web services to create value-added and personalized composite services. As web services with similar functionality are expected to be provided by competing providers, a key challenge is to find the “best” web services to participate in the composition. When multiple quality aspects (e.g., response time, fee, etc.) are considered, a weighting mechanism is usually adopted by most existing approaches, which requires users to specify their preferences as numeric values. We propose to exploit the dominance relationship among service providers to find a set of “best” possible composite services, referred to as a composite service skyline. We develop efficient algorithms that allow us to find the composite service skyline from a significantly reduced searching space instead of considering all possible service compositions. We propose a novel bottom-up computation framework that enables the skyline algorithm to scale well with the number of services in a composition. We conduct a comprehensive analytical and experimental study to evaluate the effectiveness, efficiency, and scalability of the composite skyline computation approaches.
机译：服务组合正在成为整合现有Web服务以创建增值和个性化组合服务的有效工具。由于预计竞争性提供商将提供具有类似功能的Web服务，因此关键的挑战是找到“最佳” Web服务来参与该组合。当考虑多个质量方面（例如，响应时间，费用等）时，大多数现有方法通常采用加权机制，这要求用户将其偏好指定为数值。我们建议利用服务提供商之间的主导关系来找到一组“最佳”可能的复合服务，称为复合服务天际线。我们开发了有效的算法，使我们能够从大大减少的搜索空间中找到复合服务天际线，而不用考虑所有可能的服务组合。我们提出了一种新颖的自下而上的计算框架，该框架使天际线算法能够根据组合中的服务数量很好地扩展。我们进行了全面的分析和实验研究，以评估复合天际线计算方法的有效性，效率和可伸缩性。

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