This paper deals with the problem of inferring short time-scale fluctuations of a system’s behavior from periodic state measurements. In particular, we devise a novel, efficient procedure to compute four interesting performance metrics for a transient birth–death process on an interval of fixed length with given begin
and end states: the
probability to exceed a predefined (critical) level
m,
and the
expectation of the time, area,
and number of arrivals above level
m. Moreover, our procedure allows to compute the variances
and cross-correlations of the latter three metrics. The asymptotic behavior of the metrics for small
and large measurement
intervals is also derived.
An extensive numerical study in the context of communication networks reveals the impact of important system parameters on the considered performance metrics, and shows that the three latter metrics are very highly correlated. We also illustrate through this numerical study how our analysis can be used in practical situations to support e.g., capacity management and sla verification.