基于QoS的Web服务选择方法研究新进展*

随着服务计算、云计算技术的迅速发展，具有相同或相似功能但服务质量（QoS）不同的可用服务已大规模部署在互联网上。如何从这些海量Web服务中为服务组合选择令人满意的服务成了一个重要的研究问题，其选择方法是影响组合服务的QoS 和服务组合性能高低的关键因素。为了解决该问题，研究者们已开发了许多服务选择方法以帮助用户选择合适的服务。针对近五年基于QoS的Web服务选择方法的新进展进行了综述。归纳了包括运用Skyline计算、协同过滤、优化算法、多属性决策支持理论和混合方法等一些典型的服务选择方法，讨论了各方法的优势和局限性，并根据当前研究现状，探讨了该领域的发展趋势和未来研究方向和挑战。

Recent advances in approaches of web service selection based on QoS

With the rapid development of service computing and cloud computing, a tremendous amount of available services which provide the same or similar functionality but differ in quality of service (QoS) are deployed on the internet. It has become an important research problem that how to select satisfactory services for service composition from these massive services, its selection approach is a key factor which can affect the QoS of composite service and the performance of service composition. To address this problem, researchers have developed many service selection approaches to help users choose the appropriate service. This paper surveys the newly development approaches of Web service selection based on QoS in nearly five years. It summarizes some typical approaches of Web service selection based on QoS, including service selection approaches using Skyline computing, collaborative filtering, optimization algorithm, multi-attribute decision support theory, hybrid method and so on, and it also discusses advantages and limitations of each approach. Finally, this paper presents some promising directions, challenges and development trends for future research in this area according to the current status of research.