Abstract

Poisson arrivals see time averages (PASTA) is a well-known property applicable to many stochastic systems. In active probing, PASTA is invoked to justify the sending of probe packets (or trains) at Poisson times in a variety of contexts. However, due to the diversity of aims and analysis techniques used in active probing, the benefits of Poisson-based measurement, and the utility and role of PASTA, are unclear. Using a combination of rigorous results and carefully constructed examples and counterexamples, we map out the issues involved and argue that PASTA is of very limited use in active probing. In particular, Poisson probes are not unique in their ability to sample without bias. Furthermore, PASTA ignores the issue of estimation variance and the central need for an inversion phase to estimate the quantity of interest based on what is directly observable. We give concrete examples of when Poisson probes should not be used, explain why, and offer initial guidelines on suitable alternative sending processes.

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