关键词: 服务组合, 任务粒化, 分层模型, PSO

Abstract: Under the background of big service, more and more resources are released and utilized in the form of services. Meanwhile, the users' requirements grow in complexity, which leads to the exponential growth of the service composition calculation scale. In this paper, a task-granulating algorithm called TgA is proposed to solve large-scale service composition optimization problem quickly and effectively. Firstly, we build a hierarchical service composition model based on task granulation, and analyze its computational complexity. Secondly, we analyze the feasibility theoretically during the task-granulating according to the calculation of existing QoS attributes. Finally, a large number of simulation experimental results show that, compared to the classical particle swarm optimization (PSO) algorithm, the proposed algorithm can improve the service composition optimization performance by 4 to 7 times and increase the optimization accuracy by more than 10%.

Key words: service composition (SC), task granulating, hierarchical model, PSO