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Multi-Hop Probing Asymptotics in Available Bandwidth Estimation: Stochastic Analysis
This paper analyzes the asymptotic behavior of packet-train
probing over a multi-hop network path
carrying arbitrarily routed bursty cross-traffic flows.
We examine the statistical mean of the packet-train output dispersions and its
relationship to the input dispersion. We call this relationship the response
curve of path
. We show that the real response curve
is tightly lower-bounded by its multi-hop fluid
counterpart
, obtained when every cross-traffic flow on
is hypothetically replaced with a constant-rate fluid
flow of the same average intensity and routing pattern. The real curve
asymptotically approaches its fluid counterpart
as probing packet size or packet train length increases.
Most existing measurement techniques are based upon the single-hop fluid curve
associated with the bottleneck link in
. We note that the curve
coincides with
in a certain large-dispersion input range, but falls
below
in the remaining small-dispersion input ranges. As an
implication of these findings, we show that bursty cross-traffic in multi-hop
paths causes negative bias (asymptotic underestimation) to most existing
techniques. This bias can be mitigated by reducing the deviation of
from
using large packet size or long packet-trains. However,
the bias is not completely removable for the techniques that use the portion of
that falls below
.
author = {Xiliang Liu and Kaliappa Ravindran and Dmitri Loguinov},
title = {{Multi-Hop} Probing Asymptotics in Available Bandwidth Estimation: Stochastic Analysis},
booktitle = {Internet Measurement Conference 2005 (IMC 05)},
year = {2005},
address = {Berkeley, CA},
url = {https://www.usenix.org/conference/imc-05/multi-hop-probing-asymptotics-available-bandwidth-estimation-stochastic-analysis},
publisher = {USENIX Association},
month = oct
}