Comparing layered queuing and historical performance models of a distributed enterprise application

David A. Bacigalupo, Stephen A. Jarvis, Ligang He, Daniel P. Spooner, Graham R. Nudd

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Two common approaches for predicting the response times of distributed enterprise applications on new server architectures are solving queuing models and extrapolating from previously gathered performance data. The dynamic recalibration of a layered queuing model and a historical model is investigated experimentally using the IBM Websphere Performance Sample benchmark. It is found that these models can make predictions for new server architectures at a low recalibration overhead with accuracies of 84% and 83%, respectively. The methods are evaluated considering: model recalibration, the responsiveness of predictions, the systems which can be modelled, and ease of use given a minimal level of performance modelling expertise.

Original languageEnglish
Article number456-136
Pages (from-to)608-613
Number of pages6
JournalProceedings of the IASTED International Multi-Conference on Applied Informatics
Publication statusPublished - 2005
EventIASTED International Conference on Parallel and Distributed Computing and Networks, as part of the 23rd IASTED International Multi-Conference on Applied Informatics - Innsbruck, Austria
Duration: 15 Feb 200517 Feb 2005

Keywords

  • Distributed Enterprise Application
  • Historical Performance Modelling
  • Layered Queuing
  • Performance Evaluation

ASJC Scopus subject areas

  • Engineering(all)

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