客户端上下文感知的Web服务QoS预测方法

Client Context-Aware Prediction of QoS for Web Services

识别用户客户端的上下文特征的差异性,有助于为新用户预测Web服务Qo S,但现有研究缺乏对影响用户Qo S体验的上下文特征的系统分析.提出了一种客户端上下文感知的Web服务Qo S预测方法,该方法通过量化分析客户端的上下文特征,应用模糊层次分析法计算历史用户与当前用户的上下文相似度,并以该相似度结果为指导,结合协同过滤技术,以特征加权合成方法预测Web服务的Qo S值.通过实验对比和分析可知,该方法能有效解决"新用户问题",并提高Web服务Qo S预测的精度.

The identification of client context features between different users is helpful to predict quality of service（ Qo S） accurately. However,these context features affecting the experience quality of user have not been analyzed systematically in current studies. A client context-aware prediction approach of Qo S for Web services was proposed,in which the client context features were analyzed quantitatively.The fuzzy analytic hierarchy process method was applied to calculate context similarity between current user and history users. From that,the similarity weights fusion method was employed to predict the Qo S,integrating the collaborative filtering technology. Experiment analysis indicates that this approach can solve the new user problem and improve the accuracy of Qo S prediction of Web services effectively.