Abstract: To improve the searching speed and get optimal services compositions on large scale of semantic Web services, a quick composition approach based on service cluster and Quality of Service (QoS) was proposed. Using the pre-built service clusters, it could quickly get the candidate service set with the effectively reduced searching space and semantic comparison complexity. It could obtain more optimal compositions by filtering service with the dynamically determined threshold based on the best composition QoS in the process of composition. It adopted an effective redundancy processing method to ensure minimum redundant services were used in the composition, and a service cluster internal filtering method was used to limit the number of candidate services, that solved the operation overtime problems caused by too many compositions. The results of experiments performed on large scale service storage illustrate that the searching speed is improved dozens of times than common methods, and the effectiveness of service filtering and redundancy processing is remarkable, so that the approach can quickly get multiple QoS optimal and non-redundant service compositions, and perform well on deep hierarchy composition in service storage of millions level.

Key words: Web service composition, service cluster, Quality of Service (QoS), redundancy processing

摘要： 针对海量的语义Web 服务组合中如何提高搜索速度和获得最优组合的问题，提出了一种基于服务簇和服务质量(QoS)的快速组合方法。利用预先建立的服务簇进行服务搜索，可以有效缩小搜索空间，降低语义比较的复杂度，快速得到候选服务集合。组合过程中基于服务的最优组合QoS值动态确定阈值进行服务过滤，可以获得多个最优组合。同时采用高效的冗余处理方法保证组合中冗余服务最少，并采用服务簇内部过滤的方法限制候选服务数量，解决了因组合过多造成的运行超时问题。基于海量服务库进行实验，结果表明，服务搜索效率比普通搜索方法可提高几十倍，服务过滤和冗余处理效果明显，可快速获得多个QoS最优的无冗余组合，并且在百万级服务库进行大层次深度的组合时仍可保证良好的运行性能。

关键词: Web服务组合, 服务簇, 服务质量, 冗余处理