A Round-trip Delay Metric for IPPM
RFC 2681

quot;.
   If the timings are themselves performed by software on Src, however,
   then this software can only directly measure the time between when
   Src grabs a timestamp just prior to sending the test packet and when
   it grabs a timestamp just after having received the response packet,
   and we refer to these two points as "host times".

   Another contributor to this problem is time spent at Dst between the
   receipt there of the test packet and the sending of the response
   packet.  Ideally, this time is zero; it is explored further in the
   next section.

   To the extent that the difference between wire time and host time is
   accurately known, this knowledge can be used to correct for host time
   measurements and the corrected value more accurately estimates the
   desired (wire 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 Hinitial an
   upper bound on the uncertainty in the difference between wire time
   and host time on the Src host in sending the test packet, and
   similarly define Hfinal for the difference on the Src host in
   receiving the response packet.  We then note that these problems
   introduce a total uncertainty of Hinitial + Hfinal.  This estimate of
   total wire-vs-host uncertainty should be included in the
   error/uncertainty analysis of any measurement implementation.

2.7.3. Errors or Uncertainties Related to Dst Producing a Response

   Any time spent by the destination host in receiving and recognizing
   the packet from Src, and then producing and sending the corresponding
   response adds additional error and uncertainty to the round-trip
   delay measurement.  The error equals the difference between the wire

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   time the first bit of the packet is received by Dst and the wire time
   the first bit of the response is sent by Dst.  To the extent that
   this difference is accurately known, this knowledge can be used to
   correct the desired metric.  To the extent, however, that this
   difference is uncertain, this uncertainty must be accounted for in
   the error analysis of a measurement implementation. We denote this
   uncertainty by Hrefl.  This estimate of uncertainty should be
   included in the error/uncertainty analysis of any measurement
   implementation.

2.7.4. 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 because (1) some confidence level is desirable to
   be able to remove outliers, which will be found in measuring any
   physical property; and (2) a particular confidence level should be
   specified so that the results of independent implementations can be
   compared.}

   From the discussion in the previous three sections, the error in
   measurements could be bounded by determining all the individual
   uncertainties, and adding them together to form

       2*Rsource + Hinitial + Hfinal + Hrefl.

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   However, reasonable bounds on both the clock-related uncertainty
   captured by the first term and the host-related uncertainty captured
   by the last three terms should be possible by careful design
   techniques and calibrating the instruments using a known, isolated,
   network in a lab.

   The host-related uncertainties, Hinitial + Hfinal + Hrefl, 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 round-trip 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.

   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.

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   In addition to calibrating the instruments for finite delay, two
   checks should be made to ensure that packets reported as losses were
   really lost.  First, the threshold for loss should be verified.  In
   particular, ensure the "reasonable" threshold is reasonable: that it
   is very unlikely a packet will arrive after the threshold value, and
   therefore the number of packets lost over an interval is not
   sensitive to the error bound on measurements.  Second, consider the
   possibility that a packet arrives at the network interface, but is
   lost due to congestion on that interface or to other resource
   exhaustion (e.g. buffers) in the instrument.

2.8. 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 four items to consider: the Type-P of test
   packets, the threshold of infinite delay (if any), error calibration,
   and the path traversed by the test packets.  This list is not
   exhaustive; any additional information that could be useful in
   interpreting applications of the metrics should also be reported.

2.8.1. 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-Round-trip-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.

2.8.2. Loss threshold

   In addition, the threshold (or methodology to distinguish) between a
   large finite delay and loss MUST be reported.

2.8.3. Calibration Results

   +  If the systematic error can be determined, it SHOULD be removed
      from the measured values.

   +  You SHOULD also report the calibration error, e, such that the
      true value is the reported value plus or minus e, with 95%
      confidence (see the last section.)

   +  If possible, the conditions under which a test packet with finite
      delay is reported as lost due to resource exhaustion on the
      measurement instrument SHOULD be reported.

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2.8.4. Path

   Finally, the path traversed by the packet 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 on short or stable paths.  For example, 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, and the Dst host copies
   the path from Src to Dst into the corresponding reply packet, then
   the path will be precisely recorded.  This is 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.}

3. A Definition for Samples of Round-trip Delay

   Given the singleton metric Type-P-Round-trip-Delay, we now define one
   particular sample of such singletons.  The idea of the sample is to
   select a particular binding of the parameters Src, Dst, and Type-P,
   then define a sample of values of parameter T.  The means for
   defining the values of T is to select a beginning time T0, a final
   time Tf, and an average rate lambda, then define a pseudo-random
   Poisson process of rate lambda, whose values fall between T0 and Tf.
   The time interval between successive values of T will then average
   1/lambda.

   {Comment: Note that Poisson sampling is only one way of defining a
   sample.  Poisson has the advantage of limiting bias, but other
   methods of sampling might be appropriate for different situations.
   We encourage others who find such appropriate cases to use this
   general framework and submit their sampling method for
   standardization.}

3.1. Metric Name:

   Type-P-Round-trip-Delay-Poisson-Stream

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3.2. Metric Parameters:

   +  Src, the IP address of a host

   +  Dst, the IP address of a host

   +  T0, a time

   +  Tf, a time

   +  lambda, a rate in reciprocal seconds

3.3. Metric Units:

   A sequence of pairs; the elements of each pair are:

   +  T, a time, and

   +  dT, either a real number or an undefined number of seconds.

   The values of T in the sequence are monotonic increasing.  Note that
   T would be a valid parameter to Type-P-Round-trip-Delay, and that dT
   would be a valid value of Type-P-Round-trip-Delay.

3.4. Definition:

   Given T0, Tf, and lambda, we compute a pseudo-random Poisson process
   beginning at or before T0, with average arrival rate lambda, and
   ending at or after Tf.  Those time values greater than or equal to T0
   and less than or equal to Tf are then selected.  At each of the times
   in this process, we obtain the value of Type-P-Round-trip-Delay at
   this time.  The value of the sample is the sequence made up of the
   resulting <time, delay> pairs.  If there are no such pairs, the
   sequence is of length zero and the sample is said to be empty.

3.5. Discussion:

   The reader should be familiar with the in-depth discussion of Poisson
   sampling in the Framework document [1], which includes methods to
   compute and verify the pseudo-random Poisson process.

   We specifically do not constrain the value of lambda, except to note
   the extremes.  If the rate is too large, then the measurement traffic
   will perturb the network, and itself cause congestion.  If the rate
   is too small, then you might not capture interesting network
   behavior.  {Comment: We expect to document our experiences with, and
   suggestions for, lambda elsewhere, culminating in a "best current
   practices" document.}

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   Since a pseudo-random number sequence is employed, the sequence of
   times, and hence the value of the sample, is not fully specified.
   Pseudo-random number generators of good quality will be needed to
   achieve the desired qualities.

   The sample is defined in terms of a Poisson process both to avoid the
   effects of self-synchronization and also capture a sample that is
   statistically as unbiased as possible.  {Comment: there is, of
   course, no claim that real Internet traffic arrives according to a
   Poisson arrival process.}  The Poisson process is used to schedule
   the delay measurements.  The test packets will generally not arrive
   at Dst according to a Poisson distribution, nor will response packets
   arrive at Src according to a Poisson distribution, since they are
   influenced by the network.

   All the singleton Type-P-Round-trip-Delay metrics in the sequence
   will have the same values of Src, Dst, and Type-P.

   Note also that, given one sample that runs from T0 to Tf, and given
   new time values T0' and Tf' such that T0 <= T0' <= Tf' <= Tf, the
   subsequence of the given sample whose time values fall between T0'
   and Tf' are also a valid Type-P-Round-trip-Delay-Poisson-Stream
   sample.

3.6. Methodologies:

   The methodologies follow directly from:

   +  the selection of specific times, using the specified Poisson
      arrival process, and

   +  the methodologies discussion already given for the singleton Type-
      P-Round-trip-Delay metric.

   Care must, of course, be given to correctly handle out-of-order
   arrival of test or response packets; it is possible that the Src
   could send one test packet at TS[i], then send a second test packet
   (later) at TS[i+1], and it could receive the second response packet
   at TR[i+1], and then receive the first response packet (later) at
   TR[i].

3.7. Errors and Uncertainties:

   In addition to sources of errors and uncertainties associated with
   methods employed to measure the singleton values that make up the
   sample, care must be given to analyze the accuracy of the Poisson
   process with respect to the wire-times of the sending of the test
   packets.  Problems with this process could be caused by several

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   things, including problems with the pseudo-random number techniques
   used to generate the Poisson arrival process, or with jitter in the
   value of Hinitial (mentioned above as uncertainty in the singleton
   delay metric).  The Framework document shows how to use the
   Anderson-Darling test to verify the accuracy of a Poisson process
   over small time frames.  {Comment: The goal is to ensure that test
   packets are sent "close enough" to a Poisson schedule, and avoid
   periodic behavior.}

3.8. Reporting the Metric:

   You MUST report the calibration and context for the underlying
   singletons along with the stream.  (See "Reporting the metric" for
   Type-P-Round-trip-Delay.)

4. Some Statistics Definitions for Round-trip Delay

   Given the sample metric Type-P-Round-trip-Delay-Poisson-Stream, we
   now offer several statistics of that sample.  These statistics are
   offered mostly to be illustrative of what could be done.

4.1. Type-P-Round-trip-Delay-Percentile

   Given a Type-P-Round-trip-Delay-Poisson-Stream and a percent X
   between 0% and 100%, the Xth percentile of all the dT values in the
   Stream.  In computing this percentile, undefined values are treated
   as infinitely large.  Note that this means that the percentile could
   thus be undefined (informally, infinite).  In addition, the Type-P-
   Round-trip-Delay-Percentile is undefined if the sample is empty.

   Example: suppose we take a sample and the results are:

      Stream1 = <
      <T1, 100 msec>
      <T2, 110 msec>
      <T3, undefined>
      <T4, 90 msec>
      <T5, 500 msec>
      >

   Then the 50th percentile would be 110 msec, since 90 msec and 100
   msec are smaller and 110 msec and 'undefined' are larger.

   Note that if the possibility that a packet with finite delay is
   reported as lost is significant, then a high percentile (90th or
   95th) might be reported as infinite instead of finite.

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4.2. Type-P-Round-trip-Delay-Median

   Given a Type-P-Round-trip-Delay-Poisson-Stream, the median of all the
   dT values in the Stream.  In computing the median, undefined values
   are treated as infinitely large.  As with Type-P-Round-trip-Delay-
   Percentile, Type-P-Round-trip-Delay-Median is undefined if the sample
   is empty.

   As noted in the Framework document, the median differs from the 50th
   percentile only when the sample contains an even number of values, in
   which case the mean of the two central values is used.

   Example: suppose we take a sample and the results are:

      Stream2 = <
      <T1, 100 msec>
      <T2, 110 msec>
      <T3, undefined>
      <T4, 90 msec>
      >

   Then the median would be 105 msec, the mean of 100 msec and 110 msec,
   the two central values.

4.3. Type-P-Round-trip-Delay-Minimum

   Given a Type-P-Round-trip-Delay-Poisson-Stream, the minimum of all
   the dT values in the Stream.  In computing this, undefined values are
   treated as infinitely large.  Note that this means that the minimum
   could thus be undefined (informally, infinite) if all the dT values
   are undefined.  In addition, the Type-P-Round-trip-Delay-Minimum is
   undefined if the sample is empty.

   In the above example, the minimum would be 90 msec.

4.4. Type-P-Round-trip-Delay-Inverse-Percentile

   Given a Type-P-Round-trip-Delay-Poisson-Stream and a time duration
   threshold, the fraction of all the dT values in the Stream less than
   or equal to the threshold.  The result could be as low as 0% (if all
   the dT values exceed threshold) or as high as 100%.  Type-P-Round-
   trip-Delay-Inverse-Percentile is undefined if the sample is empty.

   In the above example, the Inverse-Percentile of 103 msec would be
   50%.

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5. Security Considerations

   Conducting Internet measurements raises both security and privacy
   concerns.  This memo does not specify an implementation of the
   metrics, so it does not directly affect the security of the Internet
   nor of applications which run on the Internet.  However,
   implementations of these metrics must be mindful of security and
   privacy concerns.

   There are two types of security concerns: potential harm caused by
   the measurements, and potential harm to the measurements.  The
   measurements could cause harm because they are active, and inject
   packets into the network.  The measurement parameters MUST be
   carefully selected so that the measurements inject trivial amounts of
   additional traffic into the networks they measure.  If they inject
   "too much" traffic, they can skew the results of the measurement, and
   in extreme cases cause congestion and denial of service.

   The measurements themselves could be harmed by routers giving
   measurement traffic a different priority than "normal" traffic, or by
   an attacker injecting artificial measurement traffic.  If routers can
   recognize measurement traffic and treat it separately, the
   measurements will not reflect actual user traffic.  If an attacker
   injects artificial traffic that is accepted as legitimate, the loss
   rate will be artificially lowered.  Therefore, the measurement
   methodologies SHOULD include appropriate techniques to reduce the
   probability measurement traffic can be distinguished from "normal"
   traffic.  Authentication techniques, such as digital signatures, may
   be used where appropriate to guard against injected traffic attacks.

   The privacy concerns of network measurement are limited by the active
   measurements described in this memo.  Unlike passive measurements,
   there can be no release of existing user data.

6. Acknowledgements

   Special thanks are due to Vern Paxson and to Will Leland for several
   useful suggestions.

7. References

   [1]  Paxson, D., Almes, G., Mahdavi, J. and M. Mathis, "Framework for
        IP Performance Metrics", RFC 2330, May 1998.

   [2]  Almes, G., Kalidindi,S. and M. Zekauskas, "A One-way Delay
        Metric for IPPM", RFC 2679, September 1999.

   [3]  Mills, D., "Network Time Protocol (v3)", RFC 1305, April 1992.

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   [4]  Mahdavi, J. and V. Paxson, "IPPM Metrics for Measuring
        Connectivity", RFC 2678, September 1999.

   [5]  Postel, J., "Internet Protocol", STD 5, RFC 791, September 1981.

   [6]  Bradner, S., "Key words for use in RFCs to Indicate Requirement
        Levels", BCP 14, RFC 2119, March 1997.

8. Authors' Addresses

   Guy Almes
   Advanced Network & Services, Inc.
   200 Business Park Drive
   Armonk, NY  10504
   USA

   Phone: +1 914 765 1120
   EMail: almes@advanced.org

   Sunil Kalidindi
   Advanced Network & Services, Inc.
   200 Business Park Drive
   Armonk, NY  10504
   USA

   Phone: +1 914 765 1128
   EMail: kalidindi@advanced.org

   Matthew J. Zekauskas
   Advanced Network & Services, Inc.
   200 Business Park Drive
   Armonk, NY 10504
   USA

   Phone: +1 914 765 1112
   EMail: matt@advanced.org

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9.  Full Copyright Statement

   Copyright (C) The Internet Society (1999).  All Rights Reserved.

   This document and translations of it may be copied and furnished to
   others, and derivative works that comment on or otherwise explain it
   or assist in its implementation may be prepared, copied, published
   and distributed, in whole or in part, without restriction of any
   kind, provided that the above copyright notice and this paragraph are
   included on all such copies and derivative works.  However, this
   document itself may not be modified in any way, such as by removing
   the copyright notice or references to the Internet Society or other
   Internet organizations, except as needed for the purpose of
   developing Internet standards in which case the procedures for
   copyrights defined in the Internet Standards process must be
   followed, or as required to translate it into languages other than
   English.

   The limited permissions granted above are perpetual and will not be
   revoked by the Internet Society or its successors or assigns.

   This document and the information contained herein is provided on an
   "AS IS" basis and THE INTERNET SOCIETY AND THE INTERNET ENGINEERING
   TASK FORCE DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING
   BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION
   HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED WARRANTIES OF
   MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.

Acknowledgement

   Funding for the RFC Editor function is currently provided by the
   Internet Society.

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