Research On Semantic Web Service Selection Based On QoS

With the increasing number of Web services deployed on the network,it becomes more and more difficult to describe,find and select services.People no longer satisfy the functional attributes of services,but also pay more and more attention to the non-functional attributes of services,namely,quality of service(QoS).However,the increase of the candidate services scale leads to the decrease of the efficiency of the traditional QoS-based semantic service selection algorithm.Moreover,the traditional algorithm based on QoS is not comprehensive in semantic description of QoS,it can not express the user preferences perfectly,which affects the result of service selection.Therefore,in order to quickly and accurately select the services that users need,this paper improves service selection efficiency through dynamic service filtering,expresses user preferences through fuzzy numbers,and improves traditional semantic matching algorithm based on QoS.In the last chapter,a service selection framework based on QoS is proposed.This paper mainly does the following work:(1)Based on the analysis of the characteristics and shortcomings of existing QoS ontology models,a new QoS ontology model,QoS-PN,is proposed to provide a service provider and a service requestor with a shared and unified framework,which describes quality of service.This model supports rich semantic description,has strong scalability,and add QoS description of dynamic change and personalization.The model provides the basis for QoS semantic matching and numerical matching.(2)When the number of candidate service groups is too large,it leads to inefficiency in the service selection process,and it is impossible to find the services required by the users in a short time.In addition,due to the change of network environment,the QoS attributes of Web services constantly fluctuate,and the reliability of service selection results is difficult to be guaranteed.In order to improve the efficiency and reliability of service selection in a dynamic network environment,this paper proposes a two-layer dynamic filtering model based on QoS.The first layer filters out the unstable services and reduces the size of candidate services by using the discrete coefficient method and the QoS history record.The second layer uses the branch boundary method in the Skyline algorithm to filter out redundant services to further reduce the size of the candidate service group.At the same time,according to the dynamic characteristics of the Web service environment,a Skyline automaticmaintenance algorithm is proposed to update the Skyline service set in real time.(3)Due to the user's subjective judgment and the ambiguity of the preference description,the traditional weighting method are difficult to accurately represent the user's preferences.In order to solve this problem,order analysis method(G1 method)is improved through the fuzzy number for expressing the user's subjective weight.At the same time,the subjectivity of fully subjective weighting is too strong,it ignores the relationship between attributes and attributes and the relationship between attributes and weights.This paper proposes a dynamic weight adjustment algorithm,which dynamically adjusts weights according to the association between attribute values and attribute values as well as user preferences.(4)By analyzing the characteristics of semantic QoS matching based on Ontology tree,and the traditional algorithm of QoS semantic and numerical matching is improved to boost the accuracy of QoS matching base on the model of QoS-PN,.(5)Considering several factors such as service filtering,semantic matching and personalized preference,a multi-layer semantic Web service selection framework based on QoS-PN is proposed.Experiments showed that the framework can improve the efficiency and accuracy of service selection.