Research On QoS-Aware Web Services Discovery And Composition

As a new Web pattern, Web services has been rapidly developed in recent years. With the rapid development of Web services, the number of services with similar or equal function is larger and larger,so how to utilize QoS (Quality of Service) attributions to discovery and select Web services and dynamically integrate the existent Web services to form a newly value-added and complex service to meet the functional and QoS requirement of different users is a popular research area.Our work mainly focuses on studyinging the methods of Web Services Discovery and Composition based on QoS, so as to provide business with certain quality effectively in the complex environment of Internet, according to users'requirements.The paper proposes a QoS-based Web services discovery and composition framework—WebJet2. And WebJet2 is designed for publication, management, discovery of the services, optimization prior to the composition and fault-tolerance at the running time.The paper analyzes current QoS models' advantages and disadvantages, based on which proposes an objective QoS model. The model presents the relation QoS not only computes the QoS of single service but also ensures the composite services to evaluate correctly。To resolve the problem that Web services discovery algorithm is lack of flexibilitya and the advertised QoS information of Web services is not always trust worthy, a Web services discovery model based on QoS and Reputation is presented. In addition, algorithms of matching, ranking and selection about Web service are given. A set of QoS categorization tModels is defined in the method to describe the QoS attributes and Reputation of a Web service. QoS advertisements of service providers are represented by QoS quantification values. QoS requirements of service consumers are represented by constraint and preference values.The matching rules classified three levels are defined and match functions is introduced to compute service similarity.Web services to meet the requirements of consumers arediscovered by four phase algorithm.The method is proved to be feasible and effective by high precision and efficiency of the prototype.We design a QoS-driven global optimization algorithm for services selection based on Genetic Algorithm(GA). A population diversity handling mechansim is presented to control the population evolution,primaturity is overcome effectively. It was solved that slow convergence by implementing a fine solutions reservation strategy.The genetic algorithm using a dynamic fitness function and fitness stretching method to magnify the difference among those close individual, so as to make the advantage of the outstanding individual more clearly. Studying the method of the crossover probability and mutant probability adaptive changed with the value of fitness function,thus aviod the matter of premature effectively and acclerate the speed of convergence.Theoretical analysis and experimental results indicate the feasibility and efficiency of this algorithm.Comparison with similar studies, the algorithm provides a more integrated and effective QoS scheme of services composition in dynamic environment.