Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance a...Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance assurance, ignoring domain specific or application level metrics which are also very important to service users. Industry Web service standards lack QoS expression. The support for QoS based service choice-making is very limited. We proposed an extended Web service QoS model based on configurable fuzzy synthetic evaluation system. Web service QoS is evaluated dynamically according to the service context. A QoS requirement description model is also given for service QoS requirement definition. An interactive Web service choice-making process is described, which takes QoS as a key factor when choosing from functionally equivalent services.展开更多
Web services have gained popularity m recent years anu prowue a new moue, u~ w^u, w,,,~,, ,^- cilitates interaction of scientific and business applications through the Internet. More often, several services with simil...Web services have gained popularity m recent years anu prowue a new moue, u~ w^u, w,,,~,, ,^- cilitates interaction of scientific and business applications through the Internet. More often, several services with similar functionality are available from a large and changing number of service provid- ers. Quality of Service （QoS） is the dominant factor in service selection and is of great importance to users. In this paper, we propose a model for QoS measurement and web services selection. The model consists of QoS model, QoS monitoring, QoS comparison and service selection with a QoS feedback mechanism. The most suitable service is to take into account the agreed QoS, monitoring is done during invocation phase and if any deviation is recorded, next suitable service is selected. Fi- nally the model is proved to be feasible and effective by simulation experiments.展开更多
基金Project supported by the National Natural Science Foundation of China (No. 60503041), the Hi-Tech Research and DevelopmentProgram (863) of China (No. 2004AA104340), the Chinese SemanticGrid Project, and the Science and Technology Commission ofShanghai Municipality (No. 03dz15027), China
文摘Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance assurance, ignoring domain specific or application level metrics which are also very important to service users. Industry Web service standards lack QoS expression. The support for QoS based service choice-making is very limited. We proposed an extended Web service QoS model based on configurable fuzzy synthetic evaluation system. Web service QoS is evaluated dynamically according to the service context. A QoS requirement description model is also given for service QoS requirement definition. An interactive Web service choice-making process is described, which takes QoS as a key factor when choosing from functionally equivalent services.
基金Supported by the National Natural Science Foundation of China(No.60903003)the Beijing Natural Science Foundation of China(No.4112037)the Research Fund for the Doctoral Program of Higher Education of China(No.2008000401051)
文摘Web services have gained popularity m recent years anu prowue a new moue, u~ w^u, w,,,~,, ,^- cilitates interaction of scientific and business applications through the Internet. More often, several services with similar functionality are available from a large and changing number of service provid- ers. Quality of Service （QoS） is the dominant factor in service selection and is of great importance to users. In this paper, we propose a model for QoS measurement and web services selection. The model consists of QoS model, QoS monitoring, QoS comparison and service selection with a QoS feedback mechanism. The most suitable service is to take into account the agreed QoS, monitoring is done during invocation phase and if any deviation is recorded, next suitable service is selected. Fi- nally the model is proved to be feasible and effective by simulation experiments.
