13-11-2012, 02:18 PM
Opportunistic Flow-Level Latency Estimation Using Consistent NetFlow
ABSTRACT
The inherent measurement support in routers (SNMP
counters or NetFlow) is not sufficient to diagnose
performance problems in IP networks, especially for
flow-specific problems where the aggregate behavior
within a router appears normal. Tomographic approaches
to detect the location of such problems are not feasible in
such cases as active probes can only catch aggregate
characteristics. To address this problem, in this paper, we
propose a Consistent NetFlow (CNF) architecture for
measuring per-flow delay measurements within routers.
CNF utilizes the existing NetFlow architecture that
already reports the first and last timestamps per flow, and it proposes hash-based
sampling to ensure that two adjacent routers record the
same flows. We devise a novel Multiflow estimator that
approximates the intermediate delay samples from other
background flows to significantly improve the per-flow
latency estimates compared to the naïve estimator that
only uses actual flow samples. In our experiments using
real backbone traces and realistic delay models, we show
that the Multiflow estimator is accurate with a median
relative error of less than 20% for flows of size greater
than 100 packets. We also show that Multiflow estimator
performs two to three times better than a prior approach
based on trajectory sampling at an equivalent packet
sampling rate.