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引用次数: 1
摘要
服务的相互调用和组合构成了服务互联网(Internet of services, IoS)。动态QoS是IoS的一个突出特性。现有的QoS感知方法通常将QoS作为区分同类服务的静态指标,QoS的属性相互独立,导致服务选择性能较差。本文提出了一种实时感知QoS的服务选择方法,通过基于fm的动态评价模型对实时QoS进行预测,然后采用基于哈希空间段的服务匹配算法对服务资源进行快速选择,从而找到满足用户需求的优质服务。大量的实验结果表明,挖掘QoS属性之间的动态次特征关系可以提高真实场景下的服务选择效果。
A Fast Real-Time QoS-aware Service Selection Algorithm
The mutual invocation and composition of services conduct the Internet of Services (IoS). Dynamic QoS is a prominent feature of IoS. Existing QoS-aware methods always consider the QoS as a static indicator to differentiate similar services, and attributes of QoS are independent of each other, which may lead to poor performance of service selection. In this paper, we proposed a real-time QoS-aware service selection method to find good service to match the users’ requirements, in which an FM-based dynamic evaluation model was employed to predict the real-time QoS, and then a hash space segment-based service matching algorithm is adopted to select service resources rapidly. Extensive experimental results show that mining the dynamic secondary characteristic relationship among the QoS attributes can improve the service selection effect on the real-world scene.