DocumentCode
2792212
Title
Predicting the Effect on Performance of Container-Managed Persistence in a Distributed Enterprise Application
Author
Bacigalupo, David A. ; Xue, James W J ; Hammond, Simon D. ; Jarvis, Stephen A. ; Dillenberger, Donna N. ; Nudd, Graham R.
Author_Institution
Dept. of Comput. Sci., Warwick Univ., Coventry
fYear
2007
fDate
26-30 March 2007
Firstpage
1
Lastpage
8
Abstract
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.
Keywords
Java; business data processing; distributed object management; middleware; Enterprise Java Bean-based container-managed persistence; IBM Websphere; distributed enterprise application; layered queuing performance model; middleware; server architectures; Application software; Benchmark testing; Computer architecture; Computer science; Distributed databases; Java; Middleware; Pattern recognition; Prediction methods; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Conference_Location
Long Beach, CA
Print_ISBN
1-4244-0910-1
Electronic_ISBN
1-4244-0910-1
Type
conf
DOI
10.1109/IPDPS.2007.370583
Filename
4228311
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