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.    «

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 so...    »