

Interval Parameters for Capturing Uncertainties in an EJB
Performance Model

Authors

Johannes Luethi
Institut fuer Technische Informatik, Universitaet der Bundeswehr Muenchen,
Neubiberg, Germany
Catalina M. Llado
Department of Computing, Imperial College of Science,
Technology and Medicine, London, United Kingdom

Abstract

Exact as well as approximate analytical solutions for quantitative
performance models of computer systems are usually obtained by
performing a series of arithmetical operations on the input
parameters of the model. However, especially during early phases
of system design and implementation, not all the parameter values
are usually known exactly. In related research contributions,
intervals have been proposed as a means to capture parameter
uncertainties. Furthermore, methods to adapt existing solution
algorithms to parameter intervals have been discussed. In this
paper we present the adaptation of an existing performance model
to parameter intervals. The approximate solution of a queueing
network modelling an Enterprise JavaBeans server implementation
is adapted to interval arithmetic in order to represent the
uncertainty in some of the parameters of the model. A new
interval splitting method is applied to obtain reasonable tight
performance measure intervals. Monotonicity properties of
intermediate computation results are exploited to achieve a more
efficient interval solution. In addition, parts of the original
solution algorithm are modified to increase the efficiency of the
corresponding interval arithmetical solution.

