使用广义随机Petri 网(generalized stochastic Petri net, GSPN) 对具有复杂时间约束信息的大规模Web 服务组合系统进行建模时，模型难以直观理解，并且会造成状态空间爆炸. 针对此问题提出一种扩展GSPN建模方法. 将不同类型的时间约束信息分别施加于模型的位置、变迁和弧，可以简洁直观地表达系统复杂时间约束
信息. 进而提出一组应用于扩展模型的化简规则，对模型中一些常用结构进行化简，克服了GSPN 缺乏通用化简方法以及难以在保留时间约束特征前提下进行化简的问题，减小了系统模型的状态空间. 多种模型下的化简示例表明，所提方法有效降低了系统性能分析的复杂度，适用于对大多数Web 服务组合系统进行快速性能分析.

The generalized stochastic Petri net (GSPN) model for large scale Web service composition system with complex timing constraints is usually hard to understand. System performance is difficult to analyze because of the explosion of state apace. By associating different kinds of timing constraints to place, transition and arc respectively, an extended GSPN (EGSPN) model is presented to reflect such Web service composition system in a compact and comprehensible manner. Furthermore, to deal with the problem of lacking general reduction methods for GSPN and overcome the difficulty in preserving timing constraints in model reduction process, a set of reduction rules are presented to facilitate the model reduction of EGSPN for some model
structures in common use. The model state space is decreased via model reduction. Examples show that the presented method provides an effective way to reduce complexity of initial model. It can be used to rapidly analyze performance of the most Web service composition systems.