| More and more new Internet technologies emerge at the historic moment with the update and development of the network,which bring a lot of convenience to people but also make part of the network resources become redundant.Web services,as one of the most typical implementations of service-oriented architecture,can integrate enterprise IT resources into actionable,standards-based services that can be recomposed and applied.In the cloud computing environment,the complex needs of users can be solved by combining single Web services,and the quality of service is regarded as the satisfaction of users to the service combination.How to find a group of user satisfied service combination in the miscellaneous Web service resource pool is the focus and difficulty of current cloud computing research,and also the main research objective of this thesis.This thesis mainly studies how to use dynamic flying ant colony optimization to solve Web service composition problem based on quality of service.The main work is as follows:(1)The mathematical model is established according to the topology structure of Web service composition.The three service attributes of reliability,effectiveness and execution time were weighted and weighted according to the combination weighting method to obtain the fitness function,the multi-dimensional and multi-objective problem was transformed into a single objective optimization problem,and a single objective and multi-attribute service portfolio evaluation model was constructed.(2)Aiming at the defect that ant colony optimization is easy to fall into local optimal,a dynamic flying ant colony optimization is proposed by introducing flying ants and making three improvements: the flight process of flying ants is adjusted to be dynamic,and ants will fly only when the optimal solution produced by the current iteration is better than the historical optimal solution.The number of adjacent nodes is adjusted to be dynamic,which depends on the quality of the solution.Adjust the neighborhood selection to dynamic,enhance the early exploration and late development.Dynamic flying ant colony optimization can better balance exploration and development and avoid ants falling into local optimal.(3)The dynamic flying ant colony optimization is used to simulate the Web service composition problem.Aiming at data sets of different sizes,the traditional ant colony optimization,flying ant colony optimization,dynamic flying ant colony optimization,particle swarm optimization optimization,differential evolution optimization and empire competition optimization were used to compare the optimization experiments.The results show that the performance of dynamic flying ant colony optimization has certain advantages. |
