Capacity Planning for Web Services: metrics, models, and methods
Capacity Planning for Web Services: metrics, models, and methods
Learning Dynamic Bayesian Networks
Adaptive Processing of Sequences and Data Structures, International Summer School on Neural Networks, "E.R. Caianiello"-Tutorial Lectures
Autonomic Self-Optimization According to Business Objectives
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Generating a process model from a process audit log
BPM'03 Proceedings of the 2003 international conference on Business process management
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The creation of IT simulation models for uses such as capacity planning and optimization is becoming more and more widespread. Traditionally, the creation of such models required deep modeling and/or programming expertise, thus severely limiting their extensive use. Moreover, many modern intelligent tools now require simulation models in order to carry out their function. For these tools to be widely deployable, the derivation of simulation models must be made possible without requiring excessive technical knowledge. Hence we introduce a general methodology that enables an almost automatic deployment of IT simulation models, based on three fundamental principles: Modeling only at the required level of detail; modeling standard components using pre-prepared models; and automatically deriving the application-specific model details. The technical details underlying this approach are presented. In addition, a case study, showing the application of this methodology to an eCommerce site, demonstrates the applicability of this approach.