Probing for Loss: The Case Against Probe Trains.

We assess the bias and variance of active probing measurement techniques for loss in networks. We show that loss probability is best measured using isolated probes rather than with probe `trains', which contrasts with prior work which found that probe trains better estimate statistics of lossy periods.