Network Working Group V. Raisanen
INTERNET-DRAFT Nokia
Expiration Date: July 2001 G. Grotefeld
Motorola
January 2001
Network performance measurement for periodic streams
<draft-ietf-ippm-npmps-04.txt>
1. Status of this Memo
This document is an Internet-Draft and is in full conformance with
all provisions of Section 10 of RFC2026.
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This memo provides information for the Internet community. This
memo does not specify an Internet standard of any
kind. Distribution of this memo is unlimited.
2. Abstract
This document describes a sample metric suitable for application-
level IP network transport measurement for periodic streams, such as
VoIP or streaming multimedia over IP. In this document, the reader
is assumed to be familiar with the terminology of the Framework for
IP Performance Metrics RFC 2330 [1]. This document is parallel to
A One-way Delay Metric for IPPM RFC 2679 [2]. Although this document
is based on the delay metrics, other characteristics can be measured
with this approach, too. For example, packet loss rate, reordering /
out-of sequence, and successive delay variation are all additional
metrics which can be built from this baseline set of measurements.
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3. Introduction
This document discusses concepts relevant to application-level
performance measurements of an IP network. The original driver for
this work is Quality of Service of interactive periodic streams such
as multimedia conference over IP, but the idea of application-level
measurement may have a wider scope. In the following, interactive
multimedia traffic is used as an example to illustrate the concept.
A constant bit-rate (CBR), or nearly CBR, streaming (hereinafter
called periodic) multimedia bit stream may be simulated by
transmitting uniformly sized packets (or mostly uniformly sized
packets) at regular intervals through the network to be evaluated.
The "mostly uniformly sized packets" may be found in applications
that may use smaller packets during a portion of the stream (e.g.
digitally coded voice during silence periods). As noted in the
framework document [1], a sample metric using regularly spaced
singleton tests has some limitations when considered from a
general measurement point of view: only part of the network
performance spectrum is sampled. However, from the point of view of
application-level performance, this is actually good news as
explained below.
IP delivery service measurements have been discussed within the
International Telecommunications Union (ITU). A framework for IP
service level measurements (with references to the framework for IP
performance [1]) that is intended to be suitable for service planning
has been approved as I.380 [3]. The emphasis in the ITU
recommendation is on passive measurements, though not explicitly
forbidding active measurements. The present contribution proposes a
method that is usable both for service planning and end-user testing
purposes, and is based on active measurements.
3.1 Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [4].
Although RFC 2119 was written with protocols in mind, the key words
are used in this document for similar reasons. They are used to
ensure the results of measurements from two different implementations
are comparable, and to note instances when an implementation could
perturb the network.
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3.2 Considerations related to delay
For interactive multimedia sessions, end-to-end delay is an
important factor. Too large a delay reduces the quality of the
multimedia session as perceived by the participants. One approach for
managing end-to-end delays on an Internet path involving
heterogeneous link layer technologies is to use per-domain delay
quotas (e.g. 50 ms for a particular IP domain). The 50 ms would
then be included into a calculation of an end-to-end delay bound. A
practical implementation of such as scheme ought to address issues
like possibility of asymmetric delays in a route in different
directions, and sensitivity of an application to delay variations in
a given domain. There are several alternatives as to which kind of
derivative delay metric one ought to use in managing end-to-end QoS.
This question, although very interesting, is not within the scope of
this draft and is not discussed further here.
In the following, a methodology and metric are presented for
measuring media stream transport QoS in an IP domain. The
measurement results may be used in derivative metrics such as
average and maximum delays. A metric is presented that is a standard
way for performing a measurement irrespective of the possible QoS
mechanism utilized in the core network. As an example, for a QoS
mechanism without hard guarantees, measurements may be used to
ascertain that the "best" class gets the service that has been
promised for the traffic class in question. Moreover, an operator
could study the quality of a cheap, low-guarantee service
implemented using possible slack bandwidth in other classes. Such
measurements could be made either in studying the feasibility of a
new service, or on a regular basis.
The present draft seeks to formalize the measurements in such a way
that interoperable results are achieved.
3.3 Protocol level issues
The version of the Internet Protocol used in the measurement affects
(at least) packet sizes, and should be reported.
Fig.1 illustrates measurements on multiple protocol levels that
are relevant to this draft. The major focus of the present draft
is on transport quality evaluation from application point of
view. However, to properly account for quality effects of, e.g.,
operating system and codec on packet voice, it is beneficial to be
able to measure quality at IP level [5]. Link layer monitoring
provides a way of accounting for link layer characteristics such
as bit error rates.
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---------------
| application |
---------------
| transport | <--
---------------
| network | <--
---------------
| link | <--
---------------
| physical |
---------------
Fig. 1: Different possibilities for performing measurements: a
protocol view. Above, "application" refers to all layers above
L4 and is not used in the OSI sense.
In general, the results of measurements may be influenced by
individual application requirements/responses related to the
following issues:
+ Lost packets: Applications may have varying tolerance to lost
packets. Another consideration is the distribution of lost
packets (i.e. random or bursty).
+ Long delays: Many applications will consider packets delayed
longer than a certain value to be equivalent to lost packets
(i.e. real time applications).
+ Duplicate packets: Some applications may be perturbed if
duplicate packets are received.
+ Out-of-sequence: Some applications may be perturbed if packets
are received out of sequence. This may be in addition to the
possibility of exceeding the "long" delay threshold as a result
of being out of sequence. An out-of-sequence packet outcome
occurs when a single IP packet received at a DST measurement
point has a sequence number higher than that which is
expected, and therefore, the packet is OOS due to re-ordering.
+ Corrupt packet header: Most applications will probably treat a
packet with a corrupt header as equivalent to a lost packet.
+ Corrupt packet payload: Some applications (e.g. digital voice
codecs) may accept corrupt packet payload. In some cases, the
packet payload may contain application specific forward error
correction (FEC) that can compensate for some level of
corruption.
+ Spurious packet: Dst may receive spurious packets (i.e. packets
that are not sent by the Src as part of the metric). Many
applications may be perturbed by spurious packets.
Depending, e.g., on the observed protocol level, some issues listed
above may be indistinguishable from others by the application, it
may be important to preserve the distinction for the operators of
Src, Dst, and/or the intermediate network(s).
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Because of the possible errors listed above, in most cases it is
recommended to use a packet identifier for each packet generated at
Src. Identifiers for the metric sample may be those used by the
underlying transport layer (e.g. RTP sequence number) or the same
identifiers used by an application if the application to be modeled
by the metric uses an identifier. The possibility of identifier
roll-over (reuse if intentional) during a metric collected over
a "long" (application dependent) time should be observed.
If the application does not use an identifier, it may still be
useful to add identifiers to the packets in the metric sample to
help identify possible anomalies such as out of sequence packets.
This would be most useful in the case where the application
expects to receive packets in sequence, but has no capability to
identify the sequence of packets received at Dst.
3.4 Application-level measurement
In what follows, a metric is proposed for application-level network
performance measurement. In effect, the metric is an emulation of
periodic multimedia stream performance. The justification for using
realistic application metrics in the measurement:
+ The results of the measurement are automatically relevant to the
performance as perceived by the application in question.
+ All the packets in the measurement contribute to accuracy of the
estimation of performance variation at timescale that is
important to the multimedia application (packetization
interval).
+ Effects of elastic traffic (TCP) on measurement packets are
different for a sustained stream than for single packets during
overloading situations as discussed in [3].
3.5 Measurement types
Delay measurements can be one-way [2,3], paired one-way, or
round-trip [6]. Accordingly, the measurements may be performed
either with synchronized or unsynchronized Src/Dst host clocks.
Different possibilities are listed below.
The reference measurement setup for all measurement types is
shown in Fig. 2.
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----------------< IP >--------------------
| | | |
------- ------- -------- --------
| Src | | MP | | MP | | Dst |
------- |(Src)| |(Dst) | --------
------- --------
Fig. 2: Example setup for the metric usage.
An example of the use of the metric is a setup with a source host
(Src), a destination host (Dst), and corresponding measurement
points (MP(Src) and MP(Dst)) as shown in Figure 2. Separate equipment
for measurement points may be used if having Src and/or Dst conduct
the measurement may significantly affect the delay performance to be
measured. MP(Src)should be placed/measured close to the egress point
of packets from Src. MP(Dst) should be placed/measure close to
the ingress point of packets for Dst. "Close" is defined as a
distance sufficiently small so that application-level performance
characteristics measured (such as delay) can be expected to follow
the corresponding performance characteristic between Src and Dst to
an adequate accuracy. Basic principle here is that measurement
results between MP(Src) and MP(Dst) should be the same as for a
measurement between Src and Dst, within the general error margin
target of the measurement (e.g., < 1 ms; number of lost packets is
the same). If this is not possible, the difference between MP-MP
measurement and Src-Dst measurement should preferably be systematic.
The test setup just described fulfills two important criteria:
1) Test is made with realistic stream metrics, emulating - for example -
a full-duplex Voice over IP (VoIP) call.
2) Either one-way or round-trip characteristics may be obtained.
It is also possible to have intermediate measurement points between
MP(Src) and MP(Dst), but that is beyond the scope of this document.
3.5.1 One way measurement
In the interests of specifying metrics that are as generally usable
as possible, application-level measurements based on one-way delays
are used in the example metrics. The implication of application-level
measurement for bi-directional applications such as interactive
multimedia conferencing is discussed below.
Performing a single one-way measurement only yields information on
network behavior in one direction. Moreover, the stream at the
network transport level does not emulate accurately a full-duplex
multimedia connection.
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3.5.2 Paired one way measurement
Paired one way delay refers to two multimedia streams: Src to Dst
and Dst to Src for the same Src and Dst. By way of example, for
some applications, the delay performance of each one way path is
more important than the round trip delay. This is the case for
delay-limited signals such as VoIP. Possible reasons for the
difference between one-way delays is different routing of streams
from Src to Dst vs. Dst to Src.
For example, a paired one way measurement may show that Src to Dst
has an average delay of 30ms while Dst to Src has an average delay
of 120ms. To a round trip delay measurement, this example would
look like an average of 150ms delay. Without the knowledge of the
asymmetry, we might miss a problem that the application at either
end may have with delays averaging more than 100ms.
Moreover, paired one way delay measurement emulates a full-duplex
VoIP call more accurately than a single one-way measurement only.
3.5.3 Round trip measurement
From the point of view of periodic multimedia streams,
round-trip measurements have two advantages: they avoid the need of
host clock synchronization and they allow for a simulation of
full-duplex connections. The former aspect means that a measurement
is easily performed, since no special equipment or NTP setup is
needed. The latter property means that measurement streams are
transmitted in both directions. Thus, the measurement provides
information on quality of service as experienced by appropriate
application.
The downsides of round-trip measurement are the need for more
bandwidth than an one-way test and more complex accounting of
packet loss. Moreover, the stream that is returning towards the
original sender may be more bursty than the one on the first "leg" of
the round-trip journey. The last issue, however, means in practice
that returning stream experiences worse QoS than the other one, and
the performance estimates thus obtained are pessimistic ones. The
possibility of asymmetric routing and queuing must be taken into
account during analysis of the results.
Please note that with suitable arrangements, round-trip measurements
may be performed using paired one way measurements.
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4 Sample metric for multimedia stream simulation
The sample metric presented here is similar to the sample metric
Type-P-One-way-Delay-Poisson-Stream presented in [2]. "Singletons", as
defined in [1] and [2] are not directly used in this document because
certain key results (such as duplicate or out of sequence packets)
cannot be identified in the context of a singleton, but only as part
of a sample.
4.1 Metric name
Type-P-One-way-Delay-Periodic-Stream
4.2 Metric parameters
4.2.1 Global metric parameters
These parameters are applicable to the metrics collected in the
following sections (4.2.2, 4.2.3, and 4.2.4).
+ Src, the IP address of a host
+ Dst, the IP address of a host
+ IPV, the IP version (IPv4/IPv6) used in the measurement
+ T0, a time, for starting to generate packets and taking
measurements for a sample
+ Tf, a time, greater than T0, for stopping generation of packets
for a sample
+ incT, nominal duration of inter-packet interval
+ packet size p(j), the number of bytes in each packet of Type-P of
size j
+ dTloss, a time interval, used for determining if a packet should
be considered lost
+ Tcons, a time interval [optional]
While a number of applications will use one packet size (j = 1),
other applications may use packets of different sizes (j > 1).
Especially in cases of congestion, it may be useful to have
packets smaller than the maximum or predominant size of packets
in the periodic stream.
4.2.2 Metrics collected at MP(Src)
+ Tstamp(Src)[i], for each packet [i], the time of the packet as
measured at MP(Src)
+ PktID [i], for each packet [i], an identification number for the
the packet sent from Src to Dst.
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+ PktSiTy [i], for each packet [i], the packet size and/or type.
Some applications may use packets of different size, either
because of application requirements or in response to IP
performance experienced.
4.2.3 Metrics collected at MP (Dst)
+ dTstop, a time interval, used to add to time Tf to determine when to
stop collecting metrics for a sample
+ Tstamp(Dst)[i], for each packet [i], the time of the packet as
measured at MP(Dst)
+ PktID [i], for each packet [i], an identification number for the
the packet received at Dst from Src.
+ PktSiTy [i], for each packet [i], the packet size and/or type.
Some applications may use packets of different size, either
because of application requirements or in response to IP
performance experienced.
+ PktStatus [i], for each packet [i], the status of the packet
received. Possible status includes: OK, packet header corrupt,
packet payload corrupt, spurious, duplicate, out-of-sequence.
4.2.4 Metrics resulting when metrics collected at MP(Src) and MP(Dst)
are merged
These parameters are only available as a complete set when the
parameters from the preceding sections (4.2.1, 4.2.2, and 4.2.3 are
combined.
+ Tstamp(Src)[i], for each packet [i], the time of the packet as
measured at MP(Src). This entry may be blank or noted as N/A
for spurious packets received at MP(Dst)
+ Tstamp(Dst)[i], for each packet [i], the time of the packet as
measured at MP(Dst). This entry may be blank or noted as N/A
for packets not received at MP(Dst), received with corrupt
packet headers, or for duplicate packets received at MP(Dst).
+ PktID [i], for each packet [i], an identification number for the
the packet received. This identification number may be corrupted
for certain packets received at MP (Dst).
+ PktSiTy [i], for each packet [i], the packet size and/or type.
+ PktStatus [i], for each packet [i], the status of the packet
received. Possible status includes: OK, packet header corrupt,
packet payload corrupt, spurious, duplicate, out-of-sequence.
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+ Delay [i], for each packet [i], the time interval Tstamp(Dst)[i] -
Tstamp(Src)[i]. For the following conditions, it will not be
possible to be able to compute delay:
Spurious: There will be no Tstamp(Src)[i] time
Not received: There will be no Tstamp (Dst) [i]
Corrupt packet header: There will be no Tstamp (Dst) [i]
Duplicate: Only the first non-corrupt copy of the packet
received at Dst should have Delay [i] computed.
+ SDV[i] [optional] , for each packet [i] except the first one:
momentary delay variation between successive packets, i.e., the
time interval Delay[i] - Delay [i-1]. SDV[i] may be negative,
zero, or positive. Delay for both packets i and i+1 must be
calculable according to the definition above or SDV[i] is
undefined.
4.3 High level description of the procedure to collect a sample
Beginning on or after time T0, Type-P packets are generated
by Src and sent to Dst until time Tf is reached with a nominal
interval between the first bit of successive packets of incT as
measured at MP(Src). incT may be nominal due to a number of reasons:
variation in packet generation at Src, clock issues (see section 4.6),
etc.
MP(Src) records the following information only for packets with
timestamps between and including T0 and Tf: timestamp,
packet identifier, and packet size/type of each packet sent from Src
to Dst that is part of the sample.
MP (Dst) records the following information only for packets with
time stamps between T0 and (Tf+ dTstop): timestamp, packet identifier,
packet size/type, and received status of each packet received from
Src at Dst that is part of the sample. Optionally, at a time Tf +
Tcons, the data from MP(Src) and MP(Dst) are consolidated to derive
the results of the sample metric.
To prevent stopping data collection too soon, dTcons should be greater
than or equal to dTstop. Conversely, to keep data collection
reasonably efficient, dTstop should be some reasonable time interval
(seconds/minutes/hours), even if dTloss is infinite or extremely long.
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4.4 Discussion
The sample metric thus defined is intended to probe the delays and
the delay variation as experienced by multimedia streams of
an application. Due to the definition of the metric, also packet loss
status of packets is recorded. The delay is assumed to be measured at
transport layer level. Since a range of packet sizes and nominal
interval between packets is used, the method probes only a specific
time scale of network QoS variations.
There are a number of factors that should be taken into account when
collecting a sample metric of Type-P-One-way-Delay-Periodic-Stream.
+ T0 and (Tf + dTloss) should specify a long enough time interval to
represent a reasonable use of the application under test (e.g. do
not provide only a 100 ms time interval for a phone call)
+ T0 and (Tf + dTloss) should specify a time interval that is not
excessively long compared to the usage of the application under test
(e.g. do not provide a one week continuous phone call)
+ The nominal interval between packets (incT) and the packet size(s)
(p(j)) should not define an equivalent bit rate that is in excess
of the capacity of the egress port of Src, the ingress port of Dst,
or the carrying capacity of the intervening network(s). There may
be exceptional cases to test the response of the application to
overload conditions in the transport networks, but these cases
should be strictly controlled.
+ Real delay values will be positive. Therefore, it does not make
sense to report a negative value as a real delay. However, an
individual zero or negative delay value might be useful as part of
a stream when trying to discover a distribution of the delay values
of a stream.
+ Depending on measurement topology, delay values may be as low as
100 usec to 10 msec, whereby it may be important for Src and Dst to
synchronize very closely. GPS systems afford one way to achieve
synchronization to within several 10s of usec. Ordinary application
of NTP may allow synchronization to within several msec, but this
depends on the stability and symmetry of delay properties among those
NTP agents used, and this delay is what we are trying to measure. A
combination of some GPS-based NTP servers and a conservatively
designed and deployed set of other NTP servers should yield good
results, but this is yet to be tested.
+ Reordering of packets is best discussed in terms of the entire
set of measurement packets received, i.e. should be addressed in
Sec. 4.9.1.
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+ A given methodology will have to include a way to determine
whether packet was lost or whether delay is merely very large (and
the packet is yet to arrive at Dst). The global metric parameter
dTloss defines a time interval such that delays larger than dTloss
are interpreted as losses.
{Comment: Note that, for many applications of these metrics, the
harm in treating a large delay as infinite might be zero or very
small. A TCP data packet, for example, that arrives only after
several multiples of the RTT may as well have been lost.}
4.5 Additional Methodology Aspects
As with other Type-P-* metrics, the detailed methodology will depend
on the Type-P (e.g., protocol number, UDP/TCP port number, size,
precedence).
4.6 Errors and uncertainties
The description of any specific measurement method should include an
accounting and analysis of various sources of error or uncertainty.
The Framework document [1] provides general guidance on this point,
but we note here the following specifics related to periodic
streams and delay metrics:
+ Error due to variation of incT. The reasons for this can be e.g.
uneven process scheduling, possibly due to CPU load.
+ Errors or uncertainties due to uncertainties in the clocks of the
MP(Src) and MP(Dst) measurement points.
+ Errors or uncertainties due to the difference between 'wire time'
and 'host time'.
4.6.1. Errors or uncertainties related to Clocks
The uncertainty in a measurement of one-way delay is related, in
part, to uncertainties in the clocks of MP(Src) and MP(Dst). In
the following, we refer to the clock used to measure when the packet
was measured at MP(Src) as the MP(Src) clock and we refer to the
clock used to measure when the packet was received at MP(Dst) as the
MP(Dst) clock. Alluding to the notions of synchronization, accuracy,
resolution, and skew, we note the following:
+ Any error in the synchronization between the MP(Src) clock and
the MP(Dst) clock will contribute to error in the delay
measurement. We say that the MP(Src) clock and the MP(Dst)
clock have a synchronization error of Tsynch if the MP(Src) clock
is Tsynch ahead of the MP(Dst) clock. Thus, if we know the
value of Tsynch exactly, we could correct for clock
synchronization by adding Tsynch to the uncorrected value of
Tstamp(Dst)[i] - Tstamp(Src) [i].
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+ The accuracy of a clock is important only in identifying the time
at which a given delay was measured. Accuracy, per se, has no
importance to the accuracy of the measurement of delay. When
computing delays, we are interested only in the differences
between clock values, not the values themselves.
+ The resolution of a clock adds to uncertainty about any time
measured with it. Thus, if the MP(Src) clock has a resolution of
10 msec, then this adds 10 msec of uncertainty to any time value
measured with it. We will denote the resolution of the source
clock and the MP(Dst) clock as ResMP(Src) and ResMP(Dst),
respectively.
+ The skew of a clock is not so much an additional issue as it is a
realization of the fact that Tsynch is itself a function of time.
Thus, if we attempt to measure or to bound Tsynch, this needs to
be done periodically. Over some periods of time, this function
can be approximated as a linear function plus some higher order
terms; in these cases, one option is to use knowledge of the
linear component to correct the clock. Using this correction, the
residual Tsynch is made smaller, but remains a source of
uncertainty that must be accounted for. We use the function
Esynch(t) to denote an upper bound on the uncertainty in
synchronization. Thus, |Tsynch(t)| <= Esynch(t).
Taking these items together, we note that naive computation
Tstamp(Dst)[i] - Tstamp(Src) [i] will be off by Tsynch(t) +/-
(ResMP(SRc) + ResMP(Dst)). Using the notion of Esynch(t), we note
that these clock-related problems introduce a total uncertainty of
Esynch(t)+ Rsource + Rdest. This estimate of total clock-related
uncertainty should be included in the error/uncertainty analysis of
any measurement implementation.
4.6.2. Errors or uncertainties related to Wire-time vs Host-time
As we have defined one-way periodic delay, we would like to measure
the time between when a packet is measured and time-stamped at
MP(Src) and when it arrives and is time-stamped at MP(Dst) and we
refer to these as "wire times." If the timings are themselves
performed by software on Src and Dst, however, then this software can
only directly measure the time between when Src generates the packet
just prior to sending the test packet and when Dst has started to
process the packet after having received the test packet, and we refer
to these two points as "host times".
To the extent that the difference between wire time and host time is
accurately known, this knowledge can be used to correct for wire time
measurements and the corrected value more accurately estimates the
desired (host time) metric.
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To the extent, however, that the difference between wire time and
host time is uncertain, this uncertainty must be accounted for in an
analysis of a given measurement method. We denote by Hsource an
upper bound on the uncertainty in the difference between wire time
of MP(Src) and host time on the Src host, and similarly define Hdest
for the difference between the host time on the Dst host and the wire
time of MP(Dst). We then note that these problems introduce a total
uncertainty of Hsource+Hdest. This estimate of total wire-vs-host
uncertainty should be included in the error/uncertainty analysis of
any measurement implementation.
4.6.3. Calibration
Generally, the measured values can be decomposed as follows:
measured value = true value + systematic error + random error
If the systematic error (the constant bias in measured values) can be
determined, it can be compensated for in the reported results.
reported value = measured value - systematic error
therefore
reported value = true value + random error
The goal of calibration is to determine the systematic and random
error generated by the instruments themselves in as much detail as
possible. At a minimum, a bound ("e") should be found such that the
reported value is in the range (true value - e) to (true value + e)
at least 95 percent of the time. We call "e" the calibration error
for the measurements. It represents the degree to which the values
produced by the measurement instrument are repeatable; that is, how
closely an actual delay of 30 ms is reported as 30 ms. {Comment: 95
percent was chosen due to reasons discussed in [2], briefly
summarized as (1) some confidence level is desirable to be able to
remove outliers, which will be found in measuring any physical
property; (2) a particular confidence level should be specified so
that the results of independent implementations can be compared.}
From the discussion in the previous two sections, the error in
measurements could be bounded by determining all the individual
uncertainties, and adding them together to form
Esynch(t) + ResMP(Src) + ResMP(Dst) + Hsource + Hdest.
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However, reasonable bounds on both the clock-related uncertainty
captured by the first three terms and the host-related uncertainty
captured by the last two terms should be possible by careful design
techniques and calibrating the instruments using a known, isolated,
network in a lab.
For example, the clock-related uncertainties are greatly reduced
through the use of a GPS time source. The sum of Esynch(t) +
ResMP(Src) + ResMP(Dst) is small, and is also bounded for the
duration of the measurement because of the global time source.
The host-related uncertainties, Hsource + Hdest, could be bounded by
connecting two instruments back-to-back with a high-speed serial link
or isolated LAN segment. In this case, repeated measurements are
measuring the same one-way delay.
If the test packets are small, such a network connection has a
minimal delay that may be approximated by zero. The measured delay
therefore contains only systematic and random error in the
instrumentation. The "average value" of repeated measurements is the
systematic error, and the variation is the random error.
One way to compute the systematic error, and the random error to a
95% confidence is to repeat the experiment many times - at least
hundreds of tests. The systematic error would then be the median.
The random error could then be found by removing the systematic error
from the measured values. The 95% confidence interval would be the
range from the 2.5th percentile to the 97.5th percentile of these
deviations from the true value. The calibration error "e" could then
be taken to be the largest absolute value of these two numbers, plus
the clock-related uncertainty. {Comment: as described, this bound is
relatively loose since the uncertainties are added, and the absolute
value of the largest deviation is used. As long as the resulting
value is not a significant fraction of the measured values, it is a
reasonable bound. If the resulting value is a significant fraction
of the measured values, then more exact methods will be needed to
compute the calibration error.}
Note that random error is a function of measurement load. For
example, if many paths will be measured by one instrument, this might
increase interrupts, process scheduling, and disk I/O (for example,
recording the measurements), all of which may increase the random
error in measured singletons. Therefore, in addition to minimal load
measurements to find the systematic error, calibration measurements
should be performed with the same measurement load that the
instruments will see in the field.
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We wish to reiterate that this statistical treatment refers to the
calibration of the instrument; it is used to "calibrate the meter
stick" and say how well the meter stick reflects reality.
4.7 Reporting the metric
The calibration and context in which the metric is measured MUST be
carefully considered, and SHOULD always be reported along with metric
results. We now present five items to consider: the Type-P of test
packets, the threshold of delay equivalent to loss, error
calibration, the path traversed by the test packets, and background
conditions at Src, Dst, and the intervening networks during a sample.
This list is not exhaustive; any additional information that could be
useful in interpreting applications of the metrics should also be
reported.
4.7.1. Type-P
As noted in the Framework document [1], the value of the metric may
depend on the type of IP packets used to make the measurement, or
"type-P". The value of Type-P-One-way-Periodic-Delay could change
if the protocol (UDP or TCP), port number, size, or arrangement for
special treatment (e.g., IP precedence or RSVP) changes. The exact
Type-P used to make the measurements MUST be accurately reported.
4.7.2. Threshold for delay equivalent to loss
In addition, the threshold for delay equivalent to loss (or
methodology to determine this threshold) MUST be reported.
4.7.3. Calibration results
+ If the systematic error can be determined, it SHOULD be removed
from the measured values.
+ You SHOULD also report the calibration error, e, such that the
true value is the reported value plus or minus e, with 95%
confidence (see the last section.)
+ If possible, the conditions under which a test packet with finite
delay is reported as lost due to resource exhaustion on the
measurement instrument SHOULD be reported.
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4.7.4. Path
The path traversed by the packets SHOULD be reported, if possible.
In general it is impractical to know the precise path a given packet
takes through the network. The precise path may be known for
certain Type-P packets on short or stable paths. If Type-P includes
the record route (or loose-source route) option in the IP header,
and the path is short enough, and all routers* on the path support
record (or loose-source) route, then the path will be precisely
recorded.
This may be impractical because the route must be short enough,
many routers do not support (or are not configured for) record route,
and use of this feature would often artificially worsen the
performance observed by removing the packet from common-case
processing. However, partial information is still valuable context.
For example, if a host can choose between two links* (and hence two
separate routes from Src to Dst), then the initial link used is
valuable context. {Comment: For example, with Merit's NetNow setup,
a Src on one NAP can reach a Dst on another NAP by either of several
different backbone networks.}
4.7.5 Background conditions
In many cases, the results of a sample may be influenced by conditions
at Src, Dst, and/or any intervening networks. Some things that may
affect the results of a sample include: traffic levels and/or bursts
during the sample, link and/or host failures, etc. Information about
the background conditions may only be available by non-Internet means
(e.g. phone calls, television) and may only become available days after
samples are taken.
4.8 Single sample vs. a "sample of samples"
Because this metric represents a periodic stream as one sample, there
may be value in running multiple tests using this metric to collect
a "sample of samples". For example, it may be more appropriate to
test 1,000 two-minute VoIP calls rather than a single 2,000 minute
VoIP call. When considering collection of a sample of samples, issues
like the interval between samples (e.g. Poisson vs. periodic, time of
day/day of week), composition of samples (e.g. equal (Tf-T0 duration,
different packet sizes), and network considerations (e.g. run different
samples over different intervening link-host combinations) should be
taken into account. For items like the interval between samples,
the pattern of use of the application being measured should be
considered.
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4.9 Statistics based on Type-P-One-way-Delay-Periodic-Stream
4.9.1 Statistics calculable from one sample
As a metric based on a sample representative of certain
applications, some general purpose statistics (e.g. median and
percentile) may be less applicable than ways to characterize the
range of delay values recorded during the sample metrics.
Example, a sample metric generates 100 packets as measured at MP(Src)
with the following measurements at MP(Dst)
+ 80 packets received with delay [i] <= 20 ms
+ 8 packets received with delay [i] > 20 ms
+ 5 packets received with corrupt packet headers
+ 4 packets from MP(Src) with no matching packet recorded
at MP(Dst) (effectively lost)
+ 3 packets received with corrupt packet payload and
and delay [i] <= 20 ms
+ 2 packets that duplicate one of the 80 packets received
correctly in the first line
For this example, packets are considered acceptable if they are
received with less than or equal to 20ms delays and without corrupt
packet headers or packet payload. In this case, the percentage
of acceptable packets is 80/100 = 80%.
For a different application which will accept packets with corrupt
packet payload and no delay bound (so long as the packet is received),
the percentage of acceptable packets is (80+8+3)/100 = 91%.
4.9.2 Statistics calculable from multiple samples
For computing statistics, a "sample of samples" series of
measurements may be performed. As discussed in section 4.8, under
these conditions, general purpose statistics (e.g. median, percentile,
etc.) may be more relevant as a more statistically significant
number of packets are used.
5. Security Considerations
5.1 Denial of Service Attacks
This metric generates a periodic stream of packets from one host (Src)
to another host (Dst) through intervening networks. This metric
could be abused for denial of service attacks directed at Dst and/or
the intervening network(s).
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Administrators of Src, Dst, and the intervening network(s) should
establish bilateral or multi-lateral agreements regarding the timing,
size, and frequency of collection of sample metrics. Use of this
metric in excess the terms agreed between the participants may BE
cause for immediate rejection or discard of packets or other
escalation procedures defined between the affected parties.
5.2 User data confidentiality
This metric generates packets for a sample metric, rather than
taking samples based on user data. Thus, this metric does not
threaten user data confidentiality.
5.3 Interference with the metric
It may be possible to identify that a certain packet or stream of
packets are part of a sample metric. With that knowledge at Dst
and/or the intervening networks, it is possible to change the
processing of the packets (e.g. increasing or decreasing delay)
that may distort the measured performance. It may also be
possible to generate additional packets that appear to be part of
the sample metric. These additional packets are likely to perturb
the results of the sample measurement.
To discourage the kind of interference mentioned above, packet
interference checks, such as cryptographic hash, may be used.
6. Acknowledgements
The authors wish to thank the chairs of the IPPM WG for comments
that have made the present draft clearer and more focused. Howard
Stanislevic and Al Morton ahave presented useful comments and
questions. The authors have also built on the substantial
foundations laid by the authors of the framework for IP
performance [1].
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7. References
[1] V.Paxson, G.Almes, J.Mahdavi, and M.Mathis: Framework for IP
Performance Metrics, IETF RFC 2330, May 1998.
[2] G.Almes, S.Kalidindi, and M.Zekauskas: A one-way delay metric
for IPPM, IETF RFC 2679, September 1999.
[3] International Telecommunications Union recommendation I.380,
February 1999.
[4] S. Bradner: Key words for use in RFCs to Indicate Requirement
Levels, RFC 2119, March 1997.
[5] ETSI TIPHON document TS-101329-5 (to be published in July).
[6] G.Almes, S.Kalidindi, and M.Zekauskas: A round-trip delay
metric for IPPM, IETF RFC 2681.
8. Authors' contact information
Vilho Raisanen <Vilho.Raisanen@nokia.com>
P.O. Box 300
Nokia Networks
FIN-00045 Nokia Group
Finland
Phone +358 9 51121
Fax. +358 9 4376 8924
Glenn Grotefeld <g.grotefeld@motorola.com>
Motorola, Inc.
1303 E. Algonquin Road
4th Floor
Schaumburg, IL 60196
USA
Phone +1 847 576-5992
Fax +1 847 538-7455
EXPIRES July 2001
