Research of the Service Composition Optimization Model Based on Petri Net

Abstract

Cloud service systems bring together a wide variety of flexible and scalable mass services. The service combination scheme which can meet the user’s needs is provided to the user through the flexible and changing service mode of service combination technology. However, service combination failures often occur. In view of the above problems, this paper establishes the cloud service combination optimization model. Firstly, it is proposed that the Service Combination Optimization Petri Net models and analyzes the service selection and combination. In order to avoid local convergence, combining Service Combination Optimization Petri Net with improved Genetic Algorithm, a service combination model based on Local Search Operator Genetic Algorithm is proposed, and the legitimacy of service combination sequence is verified by Petri net. The results of experiment show that the Petri net service composition model can effectively verify the constraints of service composition and the logical rationality of the system, the Local Search Operator Genetic Algorithm effectively reduces the search space and improves the convergence rate. Compared with other algorithms, the execution efficiency and accuracy of Local Search Operator Genetic Algorithm are improved.