摘要
随着面向服务计算技术的发展,网络上出现了大量功能相同而服务质量(QoS)有很大差别的Web服务,QoS逐渐成为评价和选择Web服务的重要依据。目前常用Web服务历史QoS的算术平均值来近似服务的QoS,这种度量方法没有考虑Web服务QoS的动态性,不能准确地度量Web服务的QoS,从而造成被选择的Web服务以较大概率不能满足用户的QoS需求。针对这一问题,提出了一种基于事例推理(CBR)的QoS动态预测方法,该方法将Web服务的QoS与服务的外界环境、所处理的任务类型、任务大小关联起来,利用事例推理技术预测Web服务处理新任务时的QoS。实验结果表明,该预测方法能有效地提高Web服务QoS的准确度。
With the rapid growth of functionally similar Web services over the Web,Quality of Services（QoS） is beco-ming a decisive factor for Web service selection.However,current QoS measurement method generally takes the mean value of Web service history QoS values as the service’s QoS,and hasn’t taken the dynamic nature of service perfor-mance into consideration,and cannot measure QoS of Web services accurately,as a result,many selected services cannot satisfy consumer’s QoS constraints.In our framework,a dynamic QoS prediction method based on Case-Based Rea-soning（CBR） was provided,this method associates Web service QoS with the environment of service,task type and task size together,when a new service request comes,CBR is applied to predict QoS of the Web service in completing the new request.Experimental results show that,this method can improve accuracies of QoS of Web service effectively.
出处
《计算机科学》
CSCD
北大核心
2011年第2期119-121,137,共4页
Computer Science
基金
国家自然科学基金项目(60805022)
国家高技术研究发展计划(863)(2007AA01Z178)资助。
关键词
WEB服务选择
QoS动态预测
事例推理
Web service selection
QoS dynamic prediction
Case based reasoning
