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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].

   Internet-Drafts are working documents of the Internet Engineering
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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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   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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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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   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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