IMC '05, 2005 Internet Measurement Conference Abstract
Pp. 119124 of the Proceedings
Poisson versus Periodic Path Probing (or, Does PASTA Matter?)
Muhammad Mukarram Bin Tariq, Amogh Dhamdhere, Constantine Dovrolis, and Mostafa Ammar, Georgia Institute of Technology
The well-known PASTA (``Poisson Arrivals See Time Averages'') property
that, under very general conditions, the fraction of Poisson arrivals
that observe an underlying process in a particular state is equal,
asymptotically, to the fraction of time the process spends in that
state. When applied to network inference, PASTA implies that a Poisson
probing stream provides an unbiased estimate of the desired time
average. Our objective is to examine the practical significance of the
PASTA property in the context of realistic RTT, loss rate and packet
pair dispersion measurements with a finite (but not small) number of
samples. In particular, we first evaluate the differences between the
point estimates (median RTT, loss rate, and median dispersion) that
result from Poisson and Periodic probing. Our evaluation is based on a
rich set of measurements between 23 PlanetLab hosts. The experimental
results show that in almost all measurement sessions the differences
between the Poisson and Periodic point estimates are insignificant. In
the case of RTT and dispersion measurements, we also used a
non-parametric goodness-of-fit test, based on the Kullback-Leibler
distance, to evaluate the similarity of the distributions that result
from Poisson and Periodic probing. The results show that in more than
90% of the measurements there is no statistically significant
difference between the two distributions.
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