Finamore, Alessandro

Mellia, Marco

Trammel, B.

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[Proceeding] A Measurement-Centered Approach to Latency Reduction
Original Citation:
Trammel B., Finamore A., Mellia M. (2013). A Measurement-Centered Approach to Latency
Reduction. In: ISOC Workshop on Reducing Internet Latency, London, UK, 23 September 2013.
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A Measurement-Centered Approach to Latency Reduction
Brian Trammell, ETH Zu¨rich
Alessandro Finamore, Politecnico di Torino
Marco Mellia, Politecnico di Torino
Increasing latency on paths through the Inter-
net has a negative impact on latency-sensitive ap-
plications such as audio and video conferencing, as
well as on the perception of responsiveness of many
other applications. Measurement is key to address-
ing this issue, in two ways. First, the symptoms
of excessive latency can be hard to isolate, and the
causes obscure: the deployment of passive and ac-
tive measurements of latency is crucial to any ef-
fort to address the latency problem. Second, while
content and service providers have long attempted
to address latency issues through the development
of content delivery networks (CDNs), an empha-
sis on bandwidth as the primary measure and unit
of comparison of Internet access performance has
removed incentive for ISPs providing Internet con-
nectivity (access providers) to pay much attention
to latency.
On this second point, any effort to reduce latency
must include a re-emphasis on latency as a measure
of access performance. This, in turn, requires ad-
vances in measurement. While they may be inaccu-
rate, bandwidth measurements of access links are
easy to understand, and correlate well with per-
ceived access performance. Measuring latency is
made more difficult by the need to choose a refer-
ence point to which latency can be measured, by
nonlinear effects due to queueing, and to complex-
ity introduced by CDNs. The development of such
a metric for access provider comparison is as much
an education and awareness-raising effort as it is a
technical problem to solve; regardless, it is a neces-
sary first step to providing a powerful incentive to
reduce latency on the access segment.
The latency problem is not by any means a new
one. It impacts not just classical latency-sensitive
applications such as two-way audio and video: if
users of a website perceive too much delay in access-
ing that site, they are likely to move on. Therefore,
 0
 0.2
 0.4
 0.6
 0.8
 1
 0  20  40  60  80  100  120  140  160  180  200
CD
F
min RTT [msec]
LDNS
GoogleA
GoogleB
OpenDNS
Figure 1: Typical anomaly: DNS resolver depen-
dent latency in CDN access.
content and over-the-top service providers have de-
voted significant effort to reducing both in-network
latency as well as service response time in access
to their offerings. The development of distributed
content delivery networks (CDNs) has latency re-
duction as one of its primary goals, while increasing
complexity that makes it more difficult to diagnose
latency issues. Here, the role of measurement is to
understand the impact of these economically-driven
behaviors on the network, and to gain insight as to
where the greatest gains can be made.
To illustrate this complexity, we present an ex-
ample from a work presently under submission. We
applied Tstat [1] to passively observe latency to
several CDNs from an access network. By sep-
arating clients based on the DNS resolver they
used – that of the access provider versus Google
or OpenDNS – we verified that CDNs use the ad-
dress of the recursive resolver involved in a lookup
for a particular hostname to find the lowest-latency
location from which to serve a resource. When the
recursive resolver is located at the access provider,
the estimate of the best location is often much bet-
ter as when using a generic, nonlocal DNS resolver.
Figure 1 illustrates a possible negative effect of this
arrangement. Here we examine the CDF of the
1
minimum RTT of flows to Facebook, categorized
by the DNS resolver used by the clients, for the
entire day 22 March 2013. Non-optimal DNS host-
name to IP mapping strategies used by the CDN
on this day caused Google DNS clients to request
resources from data centers located on the other
side of the Atlantic. The effect is that clients using
local DNS resolution saw median RTTs of 20ms,
while clients using Google DNS see RTTs six times
longer.
Based on similar observations, work recently sub-
mitted to the IETF proposed to address this prob-
lem by exposing client identity information to di-
rectly to authoritative nameservers1. The guidance
produced by this result, “to reduce latency, change
your DNS provider”, is somewhat counterintuitive
based on an end-to-end model of the Internet. This
illustrates the importance of measurement in mak-
ing operational latency reduction decisions.
Measuring latency alongside bandwidth by tradi-
tional, active means without coordination has the
potential to unacceptably increase network load,
especially on mobile networks which have limited
last-mile capacity; measurement advances here in-
clude large-scale measurement coordination and
new active, passive, and hybrid measurement tech-
niques for latency estimation.
In the former category, the IETF LMAP effort
currently underway is well-placed to coordinate ac-
tive latency estimation using TWAMP or other ac-
tive measurement protocols. Beyond LMAP, the
European Commission FP7-funded mPlane con-
sortium2 is presently defining an architecture for
measurement interoperation, coordination, and au-
tomation which will have wider applicability to la-
tency measurement and diagnosis. Core to the
mPlane architecture is the notion of type equiv-
alence in measurements: that there are a wide
variety of existing measurement tools available,
which produce measurements which can be com-
pared with each other to varying degrees. By de-
noting the output of each tool with detailed infor-
mation about the types of data it produces and
consumes, mPlane allows measurements to be coor-
dinated in a multi-vendor, multi-algorithm, multi-
protocol environment.
In the latter category, there is work to be done
1http://tools.ietf.org/html/draft-vandergaast-edns-
client-subnet-01
2http://www.ict-mplane.eu
on building and deploying scalable passive meters
for latency. Here, the QoF flow meter3, based on
the production-grade YAF [2], is also under devel-
opment within the mPlane project. QoF provides
insight into the activity of TCP flows at scale by
exporting per-flow TCP dynamics information. It
is designed to support both research and network
operations, exporting IPFIX for integration with
other flow-based monitoring tools. Among other
things, it measures TCP round trip time on a per-
flow basis, using the TCP timestamp feature as
in [3] to adjust for the distance between the ob-
servation point and the sender, and heuristics to
minimize error due to application delay. For ap-
plications over TCP, this data provides a basis for
measurement of operational networks; both to un-
derstand network latency problems, as well as to
evaluate the effectiveness of latency-reduction ap-
proaches. Such large-scale passive latency estima-
tion can reduce reliance on simulations which may
not account for unmodeled interactions within the
network.
In short, latency reduction efforts can be guided,
driven, and verified by solid measurements. Indeed,
economic approaches to incentivize the deployment
of latency reduction technologies in access networks
would greatly benefit from the definition and publi-
cization of a standard, easily measurable access net-
work latency metric, though the authors acknowl-
edge the difficulty of this effort.
References
[1] A. Finamore, M. Mellia, M. Meo,
M.M.Munaf‘o, D.Rossi Experiences of In-
ternet traffic monitoring with Tstat. In Network,
vol. 25, no. 3, May–June 2011, IEEE.
[2] C. Inacio and B. Trammell YAF: Yet another
flowmeter. In Proceedings of the 24th Large In-
stallation System Administration Conference (LISA
2010) (San Jose, California, USA, Nov 2010),
USENIX Association.
[3] B. Veal, K. Li, and D. Lowenthal New
methods for passive estimation of tcp round-trip
times. In Proceedings of the 6th international
conference on Passive and Active Network Mea-
surement (Boston, 2005), PAM’05, Springer-Verlag
(LNCS 3431).
3pre-release available at http://github.com/britram/qof
2


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