Network Working Group                                        V. Raisanen
INTERNET-DRAFT                                                     Nokia
Expiration Date: November 2000                              G. Grotefeld
                                                                May 2000

            Network performance measurement for periodic streams

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 some of the issues associated with
   application-level measurements of network performance for periodic
   streams. An example application would be the testing of Dst-Src routes
   for use as bearer for multimedia streams. 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]. A sample
   metric is described that is suitable for application-level measurement
   for streaming multimedia over IP. Using such a measurement,
   transmission service of a network is probed with a traffic stream
   similar to that of the application of interest, which is likely to be
   very dissimilar to the Poisson inter-arrival interval described in [2].

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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 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",
   document are to be interpreted as described in RFC 2119 [5].
   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.

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. End-to-end
   delay may be best managed in the general case by assigning maximum
   per-domain 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.

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   For example, in estimating the delay bound that can be guaranteed for
   connections, these measurements can provide a useful tool. This is
   probably true 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

3.3 Protocol level issues

   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.
   +  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
   +  Spurious packet: Dst may receive spurious packets (i.e. packets
      that are not 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).

   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.

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   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
   +  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 [4]. 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. 1.

     ----------------< IP >--------------------
     |          |                  |          |
   -------   -------           --------    --------
   | Src |   | MP  |           | MP   |    | Dst  |
   -------   |(Src)|           |(Dst) |    --------
             -------           --------

   Fig. 1: Example setup for the metric usage.

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   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 1. 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.

   The test setup just described fulfills two important criteria:
   1) Test is made with realistic stream metrics, emulating - for example -
   a full-duplex 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.

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 voice over IP (VoIP). Possible reasons
   for the difference between one-way delays is different routing of
   streams from Src to Dst vs. Dst to Src.

   Moreover, paired one way delay measurement emulates a full-duplex
   VoIP call more accurately than a single one-way measurement only.

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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 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.

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


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
   +  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
   +  periodic packet interval incT, a time duration
   +  packet size p(j), the number of bytes in each packet of Type-P of
         size j

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   +  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
   +  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.  This identification number
      may be corrupted.
   +  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

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

   +  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).

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   +  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.
   +  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

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 4.7),

   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. Subsequently, 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.

   +  A given methodology will have to include a way to determine
      whether a delay value is infinite or whether it 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.}

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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,

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 delay metrics:

   +  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].

   +  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),

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   +  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.

   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

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   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


      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 because (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; and (3) even with a prototype user-level implementation,
   95% was loose enough to exclude outliers.}

   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.

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   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.

   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

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.

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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.

4.7.4. Path

   Finally, 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.

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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

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.

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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).

   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.

6. Acknowledgements

   The authors wish to thank the chairs of the IPPM WG, Howard
   Stanislevic and Al Morton for comments that have made the present
   draft clearer and more focused.  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] G.Almes, S.Kalidindi, and M.Zekauskas: A round-trip delay
       metric for IPPM, IETF RFC 2681.
   [5] S. Bradner: Key words for use in RFCs to Indicate Requirement
       Levels, RFC 2119, March 1997.

8. Authors' contact information

   Vilho Raisanen <>
   P.O. Box 407
   Communication Systems Laboratory
   Nokia Research Center
   FIN-00045 Nokia Group
   Phone +358 9 4376 1
   Fax. +358 9 4376 6852

   Glenn Grotefeld <>
   Motorola, Inc.
   1303 E. Algonquin Road
   4th Floor
   Schaumburg, IL 60196
   Phone  +1 847 576-5992
   Fax    +1 847 538-7455

                           EXPIRES NOVEMBER 2000