Title :
Performance Prediction and Analysis of Quality of Services for Cross-Organizational Workflows
Author :
Wen´an Tan ; Le´er Li ; Yong Sun
Author_Institution :
Sch. of Comput. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
Abstract :
Service-Oriented Architecture (SOA) promotes the combination of workflow and service composition technology, and it provides important technical supports for cross-organizational workflow applications. This paper proposes an analysis and prediction model based on time series using Particle Swarm Optimization based Back Propagation Neural Network (PSO-BPNN) model, to predict the dynamic performance of workflow systems. When the predicted value out of the preset range, we analyze the issues according to data of Quality of Service (QoS) detected at runtime, to find why cause service performance failure, which suggests more suitable recovery strategies for service composition. The results of simulation experiment have validated the effectiveness of the proposed approach.
Keywords :
backpropagation; neural nets; organisational aspects; particle swarm optimisation; quality of service; service-oriented architecture; software performance evaluation; time series; PSO-BPNN model; SOA; cross-organizational workflow applications; dynamic performance; particle swarm optimization based backpropagation neural network model; performance analysis; performance prediction; quality of services; recovery strategies; service composition technology; service performance failure; service-oriented architecture; time series; Correlation; Correlation coefficient; Mathematical model; Monitoring; Predictive models; Quality of service; Time series analysis; Cross-organizational workflow; Performance prediction; Quality of Services; Service composition;
Conference_Titel :
e-Business Engineering (ICEBE), 2014 IEEE 11th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-6562-5
DOI :
10.1109/ICEBE.2014.34
