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 language | English |
|---|---|
| Article number | 456-136 |
| Pages (from-to) | 608-613 |
| Number of pages | 6 |
| Journal | Proceedings of the IASTED International Multi-Conference on Applied Informatics |
| Publication status | Published - 2005 |
| Event | IASTED 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 2005 → 17 Feb 2005 |
Keywords
- Distributed Enterprise Application
- Historical Performance Modelling
- Layered Queuing
- Performance Evaluation
ASJC Scopus subject areas
- Engineering(all)