基于模糊多属性决策理论的语义Web服务组合算法

Fuzzy Multi-Attribute Decision Making-Based Algorithm for Semantic Web Service Composition

综合评估数据异构的服务质量(QoS)从而选择出全局最优的执行计划是语义Web服务组合研究中的难题之一.提出一种基于模糊多属性决策理论的语义Web服务组合的优化选择算法(FuMuCom)以解决上述难题.该算法能够评价以实数、区间数和语言型数据描述的QoS信息,从而进行综合决策.FuMuCom包括3个步骤:语言型数据的去模糊化、异构决策矩阵的标准化和QoS综合评估.同时还介绍了一个可扩展的本体用来描述异构的QoS数据;同时,从本体进化的角度介绍了一种异构QoS的聚合算法.最后,通过对真实的服务质量数据进行实验,验证了该算法的优越性和有效性.

Choosing the global optimal execution plan is an important process in the semantic Web service composition. The plan selection based on QoS is still challenging because the heterogeneous QoS values make data aggregation and decision making hard. This paper presents a novel Fuzzy Multi-attribute decision making-based semantic Web service Composition algorithm （FuMuCom） to solve the above difficulties for the first time. FuMuCom takes all possible QoS expression types （real number, interval and linguistic expression） into consideration. It includes three main steps： defuzzifying linguistic data, normalizing the decision matrix and evaluating alternatives synthetically. Other contributions of the paper include an extensible QoS ontology to express the heterogeneous QoS values, an ontology evolution strategy for aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach.