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Department of Computer Science

Objectives

The demands on models for performance and reliability analysis are constantly increasing, since the increasing complexity of real systems means that experiments on the system are not feasible or would require an unacceptable amount of effort. At the same time, however, the demands on the quality of results to be achieved are also increasing, so that real processes and thus also correlations must be modeled with sufficient accuracy.

The approaches available so far for adapting the parameters of a MAP to real traces still have some deficits for practical use. These deficits are to be eliminated or at least reduced within the scope of the work priorities described in the following. The goal is to perform the parameter adjustment of MAPs as efficiently and robustly as is possible with the methods for phase distributions developed in recent years.

In the second phase of the project, the extension of the developed methods for parameter fitting of MAPs to RAPs is in the foreground, in order to extend the class of models that can be analyzed with numerical methods beyond Markov processes, without having to introduce fundamentally new analysis techniques.