Performance Prediction and Analysis for Services Composition-Oriented Cross-organizational Workflow

Service-Oriented Architecture(SOA)promotes the combination of workflow technique and service composition,which provides important technical support for Cross-organizational workflow applications.According to data of Quality of Service(QoS)detected at runtime,an analysis approach based on time series is proposed using Autoregressive Integrated Moving Average(ARIMA)model to predict dynamic performance of workflow systems.When the predicted value beyond or below the setting threshold,the issues can be analyzed and the service causing performance failure can be found,to suggest more suitable recovery strategies for service composition.The results of simulation experiment show the effectiveness of the proposed approach.