结合基于qos的服务选择和性能预测

Zhengdong Gao, Gengfeng Wu
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引用次数: 47

摘要

目前,很多工作都集中在动态的、个性化的基于QoS的服务选择上,但是,目前的QoS模型一般都是由静态的QoS参数组成,没有考虑到服务性能的动态性。在我们的框架中,我们通过添加反映服务性能的新属性来扩展现有的QoS模型,并依靠人工神经网络提供客户端动态、随需应变的服务性能预测。通过这种方式,客户可能更有能力根据他/她的偏好和服务性能估计找到最佳服务
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining QoS-based service selection with performance prediction
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
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