An Investigation into the application of different performance prediction techniques to e-Commerce applications

David A. Bacigalupo*, Stephen A. Jarvis, Ligang He, Graham R. Nudd

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)
Pages3395-3402
Number of pages8
Publication statusPublished - 2004
EventProceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM) - Santa Fe, NM, United States
Duration: 26 Apr 200430 Apr 2004

Publication series

NameProceedings - International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)
Volume18

Conference

ConferenceProceedings - 18th International Parallel and Distributed Processing Symposium, IPDPS 2004 (Abstracts and CD-ROM)
Country/TerritoryUnited States
CitySanta Fe, NM
Period26/04/0430/04/04

ASJC Scopus subject areas

  • Engineering(all)

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