Research On Hybrid QoS-Aware Semantic Web Service Composition Decision Making Algorithm

As the rapid growth of Internet and WWW (World Wide Web) technologies, the internet industries are booming in recent years. WWW acts as one of the most important roles in people's lifes and business domains. Now more and more online business applications are constructed and deployed to satisfy the various customer requirments. However, the solutions owned by different corperations usually have heterogeneous interfaces, which are often tightly coupled with their inner service logics. It brings the communication difficulties among applications. Further various and numerous web applications are challenging the searching and accessing approaches. In this case, there are two basic requirments for the next generation online service model: 1. Building a loosely coupled, platform-independent, highly interoperable and scalable service paradigm. 2. Evidently improving the automatization of service activities for releasing the works of customers and developers.Semantic web service technologies aim to fulfil the expectations and requirments on the next generation internet service. Semantic web service integrates the benefits of web service and semantic web ideologies. Conceptually, web service as a novel distributed technology and an open service delivering mode brings the loosely coupled design pattern and seamless interoperability to web applications. Researches on web service focus on service discovery, service composition and QoS guarantee. Further the semantic web is a roadmap for waving cerrent web to the next generation web. On such a web, information and resources are given as knowledges. Software agents can process and integrate useful info automatically. Consequently, semantic web service promises online service logics can be executed automatically to improve the flexibility and interoperability of applications.Sevice composition is one of the most difficult aspects in the semantic web service researches. Actually, any single service only can satisfy relative simplex requirement. Service providers and customers call for existing services can be composed expediently to deliver stronger functionalities. In a service composition context, the composition engine first determines the composition pattern based on workflow design technology after user submits his functional and non-functional (mainly mean QoS in this thesis) requirements. Then service implementations are discovered by semantic functional matchmaking. After that, a large number of functional overlapping services may be yielded for each task. Each possible combination of these service candidates along the execution path is called an execution plan. Finally, a QoS (Quality of Service) -aware composition process is needed to choose the optimal plan for the composite service. Conceptually, QoS-aware composition includes QoS aggregation and final decision making. The overall QoS of each execution plan is calculated in the aggregation step and the optimal decision is made by the decision maker based on the customer QoS Constraints.Our work focuses on the QoS-aware semantic web service composition. Within our knowledges, researches on this field are underway. Several scientific problems remain: 1. The composition algorithms can not be adeptive with uncertain QoS values. 2. Can not cope with uncertain customer preferences and group decision making settings. 3. Run-time performances of existing composition algorithms decrease severely when tasks and candidate services increasing. 4. The automatization of algorithm execution is low. For solving the above difficulties, this thesis introduces a more descriptive hybrid (integrates certain and uncertain descriptions) QoS ontology, its management framework and evolution strategies. Further we introduce a hybrid QoS model-aware semantic web service composition algorithm. In addition, the implementing strategies of the composition system are discussed. Our research work has several significant contributions:1) Constructing the hybrid QoS ontology and management framework. Most current QoS models accept certain (real number-based) descriptions. This kind of model makes losing much QoS info and misleading the decision process. This thesis introduces a hybrid QoS ontology—OWL-S-QoS to describe QoS attributes more efficiently and accurately. This QoS model integrates certain and uncertain (interval type and linguistic type) expression types. Further, this thesis also presents an enhanced reputation model-WSrep to reduce the influence of maliciouse rating attack. In addition, the management framework and evolution strategies for OWL-S-QoS are also discussed, which includes defining add, modify and delete operations on concepts, a ontology chaining evolution algorithm for assuring the effectiveness and consistency of knowledge updating. The evolution algorithm includes a ontology abstract matchmaking based versioning algorithm and a hybrid QoS aggregation evolution algorithm. The simulation results show the WSrep has the strong ability to defense the malicious rating attack. Further the abstract matchmaking based ontology versioning algorithm has better performance than existing approaches.2) Presenting an Uncertain Multi-attribute decision making-based service Composion algorithm (UMC) to solve the difficulty of hybrid QoS-aware semantic web service composition. UMC aims to choose the best execution plan from a global viewpoint based on customer QoS constraints. UMC is different from other similar approaches in several ways: 1. UMC can be adapted with hybrid QoS model. 2. UMC can be used with uncertain customer preference and in group decision making scenario. 3. UMC has better run-time performance than others in large problem scales. UMC has two logical parts: UMC-Core and UMC-DH (Distributed and Heuristic framework for UMC). UMC-Core is used for assessing candidates with hybrid QoS values and includes three sequential steps: linguistic QoS defuzzification, heterogeneous QoS values normalization and synthetically evaluation. UMC-DH is designed for improving the run-time efficiency of UMC, including distributed local optimal solution finding, k-heuristic QoS aggregation for parallel structures, and global backtracking control strategy. The simulation results prove that the UMC has high decision sensitivity and stability. Further, it has better run-time performance, approximation ratio and success ratio than other similar approaches.3) Designing the UMC implementation strategies. This thesis discusses a multi-agent technology-based UMC framework for implementing the service composition approaches. It includes service composition engine (QComposer) designing, service register designing, customer agent designing and knowledge manager designing. In addition, two interaction models of involved intelligent agents are discussed: service composition interaction model and ontology evolution interaction model. This framework is a high automatic and scalable one, which brings the basic theories and technologies for implementing the service composition system.