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混合QoS模型在传统模型中加入了不确定因素用来增强其语义描述能力,为解决混合QoS模型感知的语义Web服务组合问题,提出了一种基于不确定多属性决策理论的全局优化决策算法(uncertain multi-attribute decision making-based composition algorithm,UMC).该算法分为2个部分:其中UMC-Core可用于综合评估以实数型、区间型和语言型数据描述的服务质量信息;UMC-DH(distributed and heuristic framework for UMC)是为UMC设计的分布式与启发式相结合的算法执行框架,用来解决服务组合求解空间增大时的效率问题.仿真结果证实,相比于其他类似算法,UMC算法具有较高的运行时效率、最优解近似度和最优解成功率.
In order to solve the problem of the combination of semantic Web services perceived by mixed QoS model, a hybrid QoS model is proposed by adding uncertain factors to the traditional model to enhance its semantic description ability. A global optimization decision algorithm based on the uncertain multiple attribute decision theory UMC-DH can be used to comprehensively evaluate the quality of service information described by real-type, interval-type and linguistic data. UMC-DH distributed and heuristic framework for UMC is a distributed and heuristic algorithm execution framework designed for UMC to solve the efficiency problem of service composition when space is increased.The simulation results show that compared with other similar algorithms, UMC The algorithm has high runtime efficiency, the optimal solution approximation degree and the optimal solution success rate.