Combining QoS-based service selection with performance prediction
Combining QoS-based service selection with performance prediction
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DOI：
10.1109/icebe.2005.38
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发表时间：
2005-10
期刊：
影响因子：
--
通讯作者：
Zhengdong Gao;Gengfeng Wu
中科院分区：
文献类型：
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作者：
Zhengdong Gao;Gengfeng Wu
目前，许多工作都集中在动态的，个性化的QoS服务选择，然而，现有的QoS模型通常是由静态的QoS参数，并没有考虑到服务性能的动态性质。在我们的框架中，我们扩展现有的QoS模型，通过添加新的属性，反映服务的性能，并依靠人工神经网络提供客户端的动态，按需服务的性能预测。通过这种方式，客户端可以更能够基于他/她的偏好和服务性能估计两者来找到最佳服务
Currently, much efforts have being focused on dynamic, personalized QoS-based service selection, however, current QoS models are generally composed of static QoS parameters and haven't taken the dynamic nature of service performance into consideration. In our framework, we extend existing QoS model by adding new attributes that reflect performance of services and rely on ANN to provide client dynamic, on demand service performance prediction. Through this way, a client may be more capable of finding the best service based both on his/her preferences and on the service performance estimation