Service composition based on hierarchical state machine

There have been many research methods on Web service composition, and state machine is one of them. The service composition based on the state machine is easier to understand, more intuitive and clearer than other methods. However, as the number of states increases, the jump between states will also become complicated. In this regard, a solution to the service composition based on a hierarchical state machine is proposed, which uses the service state machine to transform into a service rule library, and finally obtains the hierarchical state machine by adding default states and hierarchical generation algorithms. The reachability and equivalence verification proves that the method is feasible. Secondly, in the process of Web service composition, there are situations where multiple sub-services meet the user's functional requirements. In this case, in order to meet other non-functional requirements of users, it is necessary to filter the sub-services in the set of candidate subservices. In this regard, an improved firework particle swarm algorithm is proposed. The good point set method is introduced to initialize the particle population, which improves the diversity of the particle population at the beginning of the algorithm, and uses the particle position instead of the fitness value to improve the explosion radius formula and expand the search range of the algorithm. Improve convergence speed. In order to verify the effectiveness of the proposed algorithm, the experimental data adopts the QWS data set, and compares the improved firework particle swarm algorithm with IDPSO and FWPSO algorithms. The experimental results show that the proposed improved firework particle swarm algorithm can solve Web service composition more effectively Optimization.