中文摘要：

针对JUFrame应用服务器性能衰退情况，设计了多种类型的客户请求程序和服务器端程序，记录了各种参数共计5类36个参数；先用主成分分析方法（PCA）进行降阶处理，然后对影响应用服务器中间件性能的主要指标采用多维时间序列分析（ARX）的方法建模。实测数据进行统计分析的结果表明，用所建健康模型得到的预测值能很好地拟合原始数据，与一维AR模型相比，预测精度有明显提高，该模型可以用于系统运行时的实时预测，预测结果可作为系统后续维护动作的触发依据。

英文摘要：

An experimental scenario of testing software performance recession of JUFrame application sever system is appropriately designed in this paper. Multiple kinds of client applications and server programs are designed, and 36 parameters in 5 categories are recorded . Primary component analysis is first adopted to reduce dimension, then a model based on key performance parameter of application server middleware is set up using multi-dimensional time series analysis method. The result shows that the predict value came from the health model can simulate the original data precisely. Compared with the one-dimensional AR model,the prediction accuracy has been obviously improved. This model can be employed to predict the practical runtime system, and the predicting result can be further used as the trigger of system maintence follow-up action.