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Versions: 00 01 02 03 04 05 06 07 RFC 3432
IP Performance Measurement Working Group V.Raisanen
Internet Draft Nokia
Document: <draft-ietf-ippm-npmps-07.txt> G.Grotefeld
Category: Standards Track Motorola
A.Morton
AT&T Labs
Network performance measurement with periodic streams
Status of this Memo
This document is an Internet-Draft and is in full conformance with
all provisions of Section 10 of RFC2026 [1].
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1. Abstract
This memo describes a periodic sampling method and relevant metrics
for assessing the performance of IP networks. First, the memo
motivates periodic sampling and addresses the question of its value
as an alternative to Poisson sampling described in RFC 2330. The
benefits include applicability to active and passive measurements,
simulation of constant bit rate (CBR) traffic (typical of multimedia
communication, or nearly CBR, as found with voice activity
detection), and several instances where analysis can be simplified.
The sampling method avoids predictability by mandating random start
times and finite length tests. Following descriptions of the
sampling method and sample metric parameters, measurement methods
and errors are discussed. Finally, we give additional information on
periodic measurements including security considerations.
2. Conventions used in this document
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 [2].
Although RFC 2119 was written with protocols in mind, the key words
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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.
3. Introduction
This memo describes a sampling method and performance metrics
relevant to certain applications of IP networks. The original driver
for this work was Quality of Service of interactive periodic streams
such as multimedia conferencing over IP, but the idea of periodic
sampling and measurement has wider applicability. Interactive
multimedia traffic is used as an example below to illustrate the
concept.
Transmitting equal size packets (or mostly same-size packets)
through a network at regular intervals simulates a constant bit-rate
(CBR), or nearly CBR multimedia bit stream. Hereafter, these packets
are called periodic streams. Cases of "mostly same-size packets" may
be found in applications that have multiple coding methods (e.g.
digitally coded comfort noise during silence gaps in speech).
In the following sections, a sampling methodology and metrics are
presented for periodic streams. The measurement results may be used
in derivative metrics such as average and maximum delays. The memo
seeks to formalize periodic stream measurements to achieve
comparable results between independent implementations.
3.1 Motivation
As noted in the IPPM framework RFC 2330 [3], 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, some
applications also sample this limited performance spectrum and their
performance may be of critical interest.
Periodic sampling is useful for the following reasons:
* It is applicable to passive measurement, as well as active
measurement.
* An active measurement can be configured to match the
characteristics of media flows, and simplifies the estimation of
application performance.
* Measurements of many network impairments (e.g., delay variation,
consecutive loss, reordering) are sensitive to the sampling
frequency. When the impairments themselves are time-varying (and
the variations are somewhat rare, yet important), a constant
sampling frequency simplifies analysis.
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* Frequency Domain analysis is simplified when the samples are
equally spaced.
Simulation of CBR flows with periodic streams encourages dense
sampling of network performance, since typical multimedia flows have
10 to 100 packets in each second. Dense sampling permits the
characterization of network phenomena with short duration.
4. Periodic Sampling Methodology
The Framework RFC [3] points out the following potential problems
with Periodic Sampling:
1. The performance sampled may be synchronized with some other
periodic behavior, or the samples may be anticipated and the
results manipulated. Unpredictable sampling is preferred.
2. Active measurements can cause congestion, and periodic sampling
might drive congestion-aware senders into a synchronized state,
producing atypical results.
Poisson sampling produces an unbiased sample for the various IP
performance metrics, yet there are situations where alternative
sampling methods are advantageous (as discussed under Motivation).
We can prescribe periodic sampling methods that address the problems
listed above. Predictability and some forms of synchronization can
be mitigated through the use of random start times and limited
stream duration over a test interval. The periodic sampling
parameters produce bias, and judicious selection can produce a known
bias of interest. The total traffic generated by this or any
sampling method should be limited to avoid adverse affects on non-
test traffic (packet size, packet rate, and sample duration and
frequency should all be considered).
The configuration parameters of periodic sampling are:
+ T, the beginning of a time interval where a periodic sample is
desired.
+ dT, the duration of the interval for allowed sample start times.
+ T0, a time that MUST be selected at random from the interval
[T, T+dT] to start generating packets and taking measurements.
+ Tf, a time, greater than T0, for stopping generation of packets
for a sample (Tf may be relative to T0 if desired).
+ incT, the nominal duration of inter-packet interval, first bit to
first bit.
T0 may be drawn from a uniform distribution, or T0 = T + Unif(0,dT).
Other distributions may also be appropriate. Start times in
successive time intervals MUST use an independent value drawn from
the distribution. In passive measurement, the arrival of user media
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flows may have sufficient randomness, or a randomized start time of
the measurement during a flow may be needed to meet this
requirement.
When a mix of packet sizes is desired, passive measurements usually
possess the sequence and statistics of sizes in actual use, while
active measurements would need to reproduce the intended
distribution of sizes.
5. Sample metrics for periodic streams
The sample metric presented here is similar to the sample metric
Type-P-One-way-Delay-Poisson-Stream presented in RFC 2679[4].
Singletons defined in [3] and [4] are applicable here.
5.1 Metric name
Type-P-One-way-Delay-Periodic-Stream
5.2 Metric parameters
5.2.1 Global metric parameters
These parameters apply in all the sub-sections that follow (5.2.2,
5.2.3, and 5.2.4).
Parameters that each Singleton usually includes:
+ Src, the IP address of a host
+ Dst, the IP address of a host
+ IPV, the IP version (IPv4/IPv6) used in the measurement
+ dTloss, a time interval, the maximum waiting time for a packet
before declaring it lost.
+ packet size p(j), the desired number of bytes in the Type-P
packet, where j is the size index.
Optional parameters:
+ PktType, any additional qualifiers (transport address)
+ Tcons, a time interval for consolidating parameters collected at
the measurement points.
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 use packets
smaller than the maximum or predominant size of packets in the
periodic stream.
A topology where Src and Dst are separate from the measurement
points is assumed.
5.2.2 Parameters collected at the measurement point MP(Src)
Parameters that each Singleton usually includes:
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+ Tstamp(Src)[i], for each packet [i], the time of the packet as
measured at MP(Src)
Additional parameters:
+ PktID(Src) [i], for each packet [i], a unique identification or
sequence number.
+ PktSi(Src) [i], for each packet [i], the actual packet size.
Some applications may use packets of different sizes, either
because of application requirements or in response to IP
performance experienced.
5.2.3 Parameters collected at the measurement point MP(Dst)
+ Tstamp(Dst)[i], for each packet [i], the time of the packet as
measured at MP(Dst)
+ PktID(Dst) [i], for each packet [i], a unique identification or
sequence number.
+ PktSi(Dst) [i], for each packet [i], the actual packet size.
Optional parameters:
+ dTstop, a time interval, used to add to time Tf to determine when
to stop collecting metrics for a sample
+ PktStatus [i], for each packet [i], the status of the packet
received. Possible status includes OK, packet header corrupt,
packet payload corrupt, duplicate, fragment. The criteria to
determine the status MUST be specified, if used.
5.2.4 Sample Metrics resulting from combining parameters at MP(Src) and
MP(Dst)
Using the parameters above, a delay singleton would be calculated as
follows:
+ Delay [i], for each packet [i], the time interval
Delay[i] = Tstamp(Dst)[i] - Tstamp(Src)[i]
For the following conditions, it will not be possible to be able to
compute delay singletons:
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.
A sample metric for average delay is as follows
AveDelay = (1/N)Sum(from i=1 to N, Delay[i])
assuming all packets i= 1 though N have valid singletons.
A delay variation [5] singleton can also be computed:
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+ IPDV[i], for each packet [i] except the first one, delay
variation between successive packets would be calculated as
IPDV[I] = Delay[i] - Delay [i-1]
IPDV[i] may be negative, zero, or positive. Delay singletons for
packets i and i-1 must be calculable or IPDV[i] is undefined.
An example metric for the IPDV sample is the range:
RangeIPDV = max(IPDV[]) - min(IPDV[])
5.3 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 5.6), etc.
MP(Src) records the parameters above only for packets with
timestamps between and including T0 and Tf having the required Src,
Dst, and any other qualifiers. MP (Dst) also records for packets
with time stamps between T0 and (Tf + dTstop).
Optionally at a time Tf + Tcons (but eventually in all cases), the
data from MP(Src) and MP(Dst) are consolidated to derive the sample
metric results. 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.
5.4 Discussion
This sampling methodology is intended to quantify the delays and the
delay variation as experienced by multimedia streams of an
application. Due to the definitions of these metrics, also packet
loss status is recorded. The nominal interval between packets
assesses network performance variations on a specific time scale.
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.
+ The interval T0 to Tf should be specified to cover a long enough
time interval to represent a reasonable use of the application
under test, yet not excessively long in the same context (e.g.
phone calls last longer than 100ms, but less than one week).
+ The nominal interval between packets (incT) and the packet
size(s) (p(j)) should not define an equivalent bit rate that
exceeds the capacity of the egress port of Src, the ingress port
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of Dst, or the capacity of the intervening network(s), if known.
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 errors.
+ 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 the NTP agents used, and this delay is what we
are trying to measure.
+ 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: For many
applications, the treatment a large delay as infinite/loss will
be inconsequential. A TCP data packet, for example, that arrives
only after several multiples of the usual RTT may as well have
been lost.}
5.5 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).
5.6 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 RFC [3] 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
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'.
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5.6.1. 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].
+ 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.
5.6.2. Errors or uncertainties related to Wire-time vs Host-time
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 timestamps are
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applied 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, and visa-versa.
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.
5.6.3. 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 [4],
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.}
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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.
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.
5.6.4 Errors in incT
The nominal interval between packets, incT, can vary during either
active or passive measurements. In passive measurement, packet
headers may include a timestamp applied prior to most of the
protocol stack, and the actual sending time may vary due to
processor scheduling. For example, H.323 systems are required to
have packets ready for the network stack within 5 ms of their ideal
time. There may be additional variation from the network between the
Src and the MP(Src). Active measurement systems may encounter
similar errors, but to a lesser extent. These errors must be
accounted for in some types of analysis.
5.7 Reporting
The calibration and context in which the method is used MUST be
carefully considered, and SHOULD always be reported along with
metric results. We next 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.
5.7.1. Type-P
As noted in the Framework document [3], the value of a 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 reported.
5.7.2. Threshold for delay equivalent to loss
In addition, the threshold for delay equivalent to loss (or
methodology to determine this threshold) MUST be reported.
5.7.3. 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.)
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+ 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.
5.7.4. 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 one commercial setup, a Src on
one NAP can reach a Dst on another NAP by either of several
different backbone networks.}
6. Additional discussion on periodic sampling
Fig.1 illustrates measurements on multiple protocol levels that are
relevant to this memo. The user's focus is on transport quality
evaluation from application point of view. However, to properly
separate the quality contribution of the operating system and codec
on packet voice, for example, it is beneficial to be able to measure
quality at IP level [6]. Link layer monitoring provides a way of
accounting for link layer characteristics such as bit error rates.
---------------
| 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.
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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.
+ Reordering: Some applications may be perturbed if packets arrive
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.
+ 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).
6.1 Measurement applications
This sampling method provides a way to perform measurements
irrespective of the possible QoS mechanisms utilized in the IP
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.
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 [3]) that is intended to be suitable for service
planning has been approved as I.380 [7]. ITU-T Recommendation I.380
covers abstract definitions of performance metrics. This memo
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describes a method that is useful both for service planning and end-
user testing purposes, in both active and passive measurements.
Delay measurements can be one-way [3,4], paired one-way, or round-
trip [8]. 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.
----------------< IP >--------------------
| | | |
------- ------- -------- --------
| Src | | MP | | MP | | Dst |
------- |(Src)| |(Dst) | --------
------- --------
Fig. 2: Example measurement setup.
An example of the use of the method 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.
6.1.1 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-
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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.
6.1.2 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.
6.1.3 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
communication. 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 two-way applications.
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 may experience worse QoS than the out-going 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.
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Network performance measurement with periodic streams April 2002
Note that with suitable arrangements, round-trip measurements may be
performed using paired one way measurements.
6.2 Statistics calculable from one sample
Some statistics may be particularly relevant to applications
simulated by periodic streams, such as the range of delay values
recorded during the sample.
For example, a sample metric generates 100 packets 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
delay [i] <= 20 ms
+ 2 packets that duplicate one of the 80 packets received
correctly as indicated in the first item
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%.
6.3 Statistics calculable from multiple samples
There may be value in running multiple tests using this method to
collect a "sample of samples". For example, it may be more
appropriate to simulate 1,000 two-minute VoIP calls rather than a
single 2,000 minute call. When considering collection of multiple
samples, issues like the interval between samples (e.g. minutes,
hours), 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 usage pattern for the application of interest should be
considered.
When computing statistics for multiple samples, more general
statistics (e.g. median, percentile, etc.) may have relevance with a
larger number of packets.
6.4 Background conditions
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In many cases, the results may be influenced by conditions at Src,
Dst, and/or any intervening networks. Factors that may affect the
results 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 external means (e.g. phone
calls, television) and may only become available days after samples
are taken.
6.5 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). However, this scheme
has clear inefficiencies, and can over-constrain the problem of
achieving some end-to-end delay objective. A more flexible
implementation ought to address issues like possibility of
asymmetric delays on paths, and sensitivity of an application to
delay variations in a given domain. There are several alternatives
as to the delay statistic one ought to use in managing end-to-end
QoS. This question, although very interesting, is not within the
scope of this memo and is not discussed further here.
7. Security Considerations
7.1 Denial of Service Attacks
This method generates a periodic stream of packets from one host
(Src) to another host (Dst) through intervening networks. This
method could be abused for denial of service attacks directed at Dst
and/or the intervening network(s).
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 method in excess of 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.
7.2 User data confidentiality
Active use of this method generates packets for a sample, rather
than taking samples based on user data, and does not threaten user
data confidentiality. Passive measurement must restrict attention to
the headers of interest. Since user payloads may be temporarily
stored for length analysis, suitable precautions MUST be taken to
keep this information safe and confidential.
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Network performance measurement with periodic streams April 2002
7.3 Interference with the metric
It may be possible to identify that a certain packet or stream of
packets is part of a sample. 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.
8. IANA Considerations
Since this method and metric do not define a protocol or well-known
values, there are no IANA considerations in this memo.
9. Normative References
1 Bradner, S., "The Internet Standards Process -- Revision 3", BCP
9, RFC 2026, October 1996.
2 Bradner, S., "Key words for use in RFCs to Indicate Requirement
Levels", RFC 2119, March 1997.
3 Paxson, V., Almes, G., Mahdavi, J., and Mathis, M., "Framework
for IP Performance Metrics", RFC 2330, May 1998.
4 Almes, G., Kalidindi, S., and Zekauskas, M., "A one-way delay
metric for IPPM", RFC 2679, September 1999.
10. Informative References
5 Demichelis, C., and Chimento, P., "IP Packet Delay Variation
Metric for IPPM", work in progress.
6 "End-to-end Quality of Service in TIPHON systems; Part 5: Quality
of Service (QoS) measurement methodologies", ETSI standard TS 101
329-5 V1.1.2 (2002-01).
7 International Telecommunications Union, "Internet protocol data
communication service _ IP packet transfer and availability
performance parameters", Telecommunications Sector Recommendation
I.380 (to be re-designated Y.1540), February 1999.
8 Almes, G., Kalidindi, S., and Zekauskas, M., "A round-trip delay
metric for IPPM", IETF RFC 2681.
11. Acknowledgments
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Network performance measurement with periodic streams April 2002
The authors wish to thank the chairs of the IPPM WG (Matt Zekauskas
and Merike Kaeo) for comments that have made the present draft
clearer and more focused. Howard Stanislevic and Will Leland have
also presented useful comments and questions. We also acknowledge
Henk Uijterwaal's continued challenge to develop the motivation for
this method. The authors have built on the substantial foundation
laid by the authors of the framework for IP performance [3].
12. Author's Addresses
Vilho Raisanen
Nokia Networks
P.O. Box 300
FIN-00045 Nokia Group
Finland
Phone +358 7180 8000 Fax. +358 9 4376 6852
<Vilho.Raisanen@nokia.com>
Glenn Grotefeld
Motorola, Inc.
1501 W. Shure Drive, MS 2F1
Arlington Heights, IL 60004 USA
Phone +1 847 435-0730 Fax +1 847 632-6800
<g.grotefeld@motorola.com>
Al Morton
AT&T Labs
Room D3 - 3C06
200 Laurel Ave. South
Middletown, NJ 07748 USA
Phone +1 732 420 1571 Fax +1 732 368 1192
<acmorton@att.com>
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