Monitoring quality of service: measurement and estimation

To provide statistical guarantees of quality of service (QoS), the Internet requires a measurement infrastructure for estimating available resources from actual traffic. In this paper, we outline an algorithm that collects a histogram of the occupancy of a single-server FCFS queue at packet arrival times, and infers the loss rate and delay distribution from such measurements. Direct estimation of such QoS parameters typically leads to estimators with a large variance. To reduce this variance we fit a buffer occupancy model, a sum of exponentials, to the histogram using a weighted least-squares algorithm. Furthermore, we compute batch means to minimize the bias due to the positive correlation between measurements. In this manner, we provide an efficient and robust approach to QoS estimation.