TY - GEN
T1 - Predicting the effect on performance of container-managed persistence in a distributed enterprise application
AU - Bacigalupo, David A.
AU - Xue, James W.J.
AU - Hammond, Simon D.
AU - Jarvis, Stephen A.
AU - Dillenberger, Donna N.
AU - Nudd, Graham R.
PY - 2007
Y1 - 2007
N2 - Container-managed persistence is an essential technology as it dramatically simplifies the implementation of enterprise data access. However it can also impose a significant overhead on the performance of the application at runtime. This paper presents a layered queuing performance model for predicting the effect of adding or removing container-managed persistence to a distributed enterprise application, in terms of response time and throughput performance metrics. Predictions can then be made for new server architectures - that is, server architectures for which only a small number of measurements have been made (e.g. to determine request processing speed). An experimental analysis of the model is conducted on a popular enterprise computing architecture based on IBM Websphere, using Enterprise Java Bean-based container-managed persistence as the middleware functionality. The results provide strong experimental evidence for the effectiveness of the model in terms of the accuracy of predictions, the speed with which predictions can be made and the low overhead at which the model can be rapidly parameterised.
AB - Container-managed persistence is an essential technology as it dramatically simplifies the implementation of enterprise data access. However it can also impose a significant overhead on the performance of the application at runtime. This paper presents a layered queuing performance model for predicting the effect of adding or removing container-managed persistence to a distributed enterprise application, in terms of response time and throughput performance metrics. Predictions can then be made for new server architectures - that is, server architectures for which only a small number of measurements have been made (e.g. to determine request processing speed). An experimental analysis of the model is conducted on a popular enterprise computing architecture based on IBM Websphere, using Enterprise Java Bean-based container-managed persistence as the middleware functionality. The results provide strong experimental evidence for the effectiveness of the model in terms of the accuracy of predictions, the speed with which predictions can be made and the low overhead at which the model can be rapidly parameterised.
UR - http://www.scopus.com/inward/record.url?scp=34548801228&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2007.370583
DO - 10.1109/IPDPS.2007.370583
M3 - Conference contribution
AN - SCOPUS:34548801228
SN - 1424409101
SN - 9781424409105
T3 - Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
BT - Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
T2 - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007
Y2 - 26 March 2007 through 30 March 2007
ER -