An Investigation into the Application of Different Performance Prediction Techniques to e-Commerce Applications

摘要

Predictive performance models of e-Commerce applications will allow Grid workload managers to provide e-Commerce clients with qualities of service (QoS) whilst making efficient use of resources. This paper demonstrates the use of two 'coarse-grained' modelling approaches (based on layered queuing modelling and historical performance data analysis) for predicting the performance of dynamic e-Commerce systems on heterogeneous servers. Results for a popular e-Commerce benchmark show how request response times and server throughputs can be predicted on servers with heterogeneous CPUs at different background loads. The two approaches are compared and their usefulness to Grid workload management is considered.