A Research For The Dynamic Strategy And Optimization Algorithm Of Web Service Composition

In response to the increasing complexity of information system requirements, new software architectures were proposed unceasingly. Reusability, cross-platform, maintainability, and efficiency improvements are looked upon as key considerations. Web services became to be widely used with its platform-independent, loosely coupled, programmable features. In order to increase the reuse rate, and enhance the processing capability of the service, a single Web service in accordance with the specific business processes combined to get more targeted, more powerful new services become a subject worthy of further study.In reality, the combination of Web services is very complex. First published on the Web service with the same functional properties continued to increase the service portfolio optimization problem as the current research focus; need for efficient high-quality optimization algorithm to derive the highest user satisfaction combinations. Quality of Service (QoS) is often used as the evaluation of the merits of the important indicators. Secondly, the environment of Web services are highly dynamic, the various parameters of the same services at any time may change, the service parameter update strategy becomes very important. In addition, the diversity of user requirements and complexity of the abstract business processes are highly complex, adding to the burden of the system is not conducive to the analysis and implementation of the service composition system.This paper analyzes the problems of common Web service composition framework, in-depth study of the dynamic combination of frameworks and services portfolio optimization. The major works are as follows:1. On the basis of a combination of basic services framework, a service update mechanism-based dynamic service composition framework. The design of the service composition process, enabling the automation of Web service composition, parallelization and dynamic characteristics. Service Level Agreement describes the QoS constraints; joined the service decomposition module, service storage modules and update module, were responsible for the decomposition of complex services and storage to meet the conditions of service data, as well as the combination of the dynamic update of the program.2. Decomposition module for dynamic service composition framework for service and service to update the module, a complex service decomposition of programs and services update policy. Service decomposition scheme for complex business processes are decomposed into smaller sub-tasks, send more than one combination of modules execute in parallel, to improve efficiency. When the combination of programs in some of the sub-service failure, service updates, strategy according to the actual situation in order to select a single service updates, implementation of the program update and re-optimization of the three strategies to ensure that the eventual implementation of a combination of services available and maintain optimal. Through examples and experimental analysis results show that the strategy to offset the impact of the instability of the services on the system efficiency.3. Artificial bee colony algorithm based on Pareto dominant mechanism is proposed for solving the service composition optimization problem. In the algorithm, a new evolution operator is introduced to improve the neighborhood search strategy, as the optimization objective QoS, SLA document Statute of the constraints to solve the optimization problem. By comparing the experimental analysis, the results show that the improved algorithm in both convergence and diversity of individuals to improve.