path: root/doc/rfc/rfc5835.txt

Internet Engineering Task Force (IETF)                    A. Morton, Ed.
Request for Comments: 5835                                     AT&T Labs
Category: Informational                           S. Van den Berghe, Ed.
ISSN: 2070-1721                                           Alcatel-Lucent
                                                              April 2010

                    Framework for Metric Composition

Abstract

   This memo describes a detailed framework for composing and
   aggregating metrics (both in time and in space) originally defined by
   the IP Performance Metrics (IPPM), RFC 2330, and developed by the
   IETF.  This new framework memo describes the generic composition and
   aggregation mechanisms.  The memo provides a basis for additional
   documents that implement the framework to define detailed
   compositions and aggregations of metrics that are useful in practice.

Status of This Memo

   This document is not an Internet Standards Track specification; it is
   published for informational purposes.

   This document is a product of the Internet Engineering Task Force
   (IETF).  It represents the consensus of the IETF community.  It has
   received public review and has been approved for publication by the
   Internet Engineering Steering Group (IESG).  Not all documents
   approved by the IESG are a candidate for any level of Internet
   Standard; see Section 2 of RFC 5741.

   Information about the current status of this document, any errata,
   and how to provide feedback on it may be obtained at
   http://www.rfc-editor.org/info/rfc5835.


















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Copyright Notice

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   Without obtaining an adequate license from the person(s) controlling
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   outside the IETF Standards Process, and derivative works of it may
   not be created outside the IETF Standards Process, except to format
   it for publication as an RFC or to translate it into languages other
   than English.

























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Table of Contents

   1. Introduction ....................................................4
      1.1. Motivation .................................................4
           1.1.1. Reducing Measurement Overhead .......................4
           1.1.2. Measurement Re-Use ..................................5
           1.1.3. Data Reduction and Consolidation ....................5
           1.1.4. Implications on Measurement Design and Reporting ....6
   2. Requirements Language ...........................................6
   3. Purpose and Scope ...............................................6
   4. Terminology .....................................................7
      4.1. Measurement Point ..........................................7
      4.2. Complete Path ..............................................7
      4.3. Complete Path Metric .......................................7
      4.4. Complete Time Interval .....................................7
      4.5. Composed Metric ............................................7
      4.6. Composition Function .......................................7
      4.7. Ground Truth ...............................................8
      4.8. Interval ...................................................8
      4.9. Sub-Interval ...............................................8
      4.10. Sub-Path ..................................................8
      4.11. Sub-Path Metrics ..........................................8
   5. Description of Metric Types .....................................9
      5.1. Temporal Aggregation Description ...........................9
      5.2. Spatial Aggregation Description ............................9
      5.3. Spatial Composition Description ...........................10
      5.4. Help Metrics ..............................................10
      5.5. Higher-Order Composition ..................................11
   6. Requirements for Composed Metrics ..............................11
      6.1. Note on Intellectual Property Rights (IPR) ................12
   7. Guidelines for Defining Composed Metrics .......................12
      7.1. Ground Truth: Comparison with Other IPPM Metrics ..........12
           7.1.1. Ground Truth for Temporal Aggregation ..............14
           7.1.2. Ground Truth for Spatial Aggregation ...............15
      7.2. Deviation from the Ground Truth ...........................15
      7.3. Incomplete Information ....................................15
      7.4. Time-Varying Metrics ......................................15
   8. Security Considerations ........................................16
   9. Acknowledgements ...............................................16
   10. References ....................................................16
      10.1. Normative References .....................................16
      10.2. Informative References ...................................17









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1.  Introduction

   The IP Performance Metrics (IPPM) framework [RFC2330] describes two
   forms of metric composition, spatial and temporal.  The text also
   suggests that the concepts of the analytical framework (or A-frame)
   would help to develop useful relationships to derive the composed
   metrics from real metrics.  The effectiveness of composed metrics is
   dependent on their usefulness in analysis and applicability to
   practical measurement circumstances.

   This memo expands on the notion of composition, and provides a
   detailed framework for several classes of metrics that were described
   in the original IPPM framework.  The classes include temporal
   aggregation, spatial aggregation, and spatial composition.

1.1.  Motivation

   Network operators have deployed measurement systems to serve many
   purposes, including performance monitoring, maintenance support,
   network engineering, and reporting performance to customers.  The
   collection of elementary measurements alone is not enough to
   understand a network's behaviour.  In general, measurements need to
   be post-processed to present the most relevant information for each
   purpose.  The first step is often a process of "composition" of
   single measurements or measurement sets into other forms.
   Composition and aggregation present several more post-processing
   opportunities to the network operator, and we describe the key
   motivations below.

1.1.1.  Reducing Measurement Overhead

   A network's measurement possibilities scale upward with the square of
   the number of nodes.  But each measurement implies overhead, in terms
   of the storage for the results, the traffic on the network (assuming
   active methods), and the operation and administration of the
   measurement system itself.  In a large network, it is impossible to
   perform measurements from each node to all others.

   An individual network operator should be able to organize their
   measurement paths along the lines of physical topology, or routing
   areas/Autonomous Systems, and thus minimize dependencies and overlap
   between different measurement paths.  This way, the sheer number of
   measurements can be reduced, as long as the operator has a set of
   methods to estimate performance between any particular pair of nodes
   when needed.






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   Composition and aggregation play a key role when the path of interest
   spans multiple networks, and where each operator conducts their own
   measurements.  Here, the complete path performance may be estimated
   from measurements on the component parts.

   Operators that take advantage of the composition and aggregation
   methods recognize that the estimates may exhibit some additional
   error beyond that inherent in the measurements themselves, and so
   they are making a trade-off to achieve reasonable measurement system
   overhead.

1.1.2.  Measurement Re-Use

   There are many different measurement users, each bringing specific
   requirements for the reporting timescale.  Network managers and
   maintenance forces prefer to see results presented very rapidly, to
   detect problems quickly or see if their action has corrected a
   problem.  On the other hand, network capacity planners and even
   network users sometimes prefer a long-term view of performance, for
   example to check trends.  How can one set of measurements serve both
   needs?

   The answer lies in temporal aggregation, where the short-term
   measurements needed by the operations community are combined to
   estimate a longer-term result for others.  Also, problems with the
   measurement system itself may be isolated to one or more of the
   short-term measurements, rather than possibly invalidating an entire
   long-term measurement if the problem was undetected.

1.1.3.  Data Reduction and Consolidation

   Another motivation is data reduction.  Assume there is a network in
   which delay measurements are performed among a subset of its nodes.
   A network manager might ask whether there is a problem with the
   network delay in general.  It would be desirable to obtain a single
   value that gives an indication of the overall network delay.  Spatial
   aggregation methods would address this need, and can produce the
   desired "single figure of merit" asked for, which may also be useful
   in trend analysis.

   The overall value would be calculated from the elementary delay
   measurements, but it is not obvious how: for example, it may not be
   reasonable to average all delay measurements, as some paths (e.g.,
   those having a higher bandwidth or more important customers) might be
   considered more critical than others.






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   Metric composition can help to provide, from raw measurement data,
   some tangible, well-understood and agreed-upon information about the
   service guarantees provided by a network.  Such information can be
   used in the Service Level Agreement/Service Level Specification
   (SLA/SLS) contracts between a service provider and its customers.

1.1.4.  Implications on Measurement Design and Reporting

   If a network measurement system operator anticipates needing to
   produce overall metrics by composition, then it is prudent to keep
   that requirement in mind when considering the measurement design and
   sampling plan.  Also, certain summary statistics are more conducive
   to composition than others, and this figures prominently in the
   design of measurements and when reporting the results.

2.  Requirements Language

   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 [RFC2119].

3.  Purpose and Scope

   The purpose of this memo is to provide a common framework for the
   various classes of metrics that are composed from primary metrics.
   The scope is limited to the definitions of metrics that are composed
   from primary metrics using a deterministic function.  Key information
   about each composed metric is included, such as the assumptions under
   which the relationship holds and possible sources of
   error/circumstances where the composition may fail.

   At this time, the scope of effort is limited to composed metrics for
   packet loss, delay, and delay variation, as defined in [RFC2679],
   [RFC2680], [RFC2681], [RFC3393], [RFC5481], and the comparable
   metrics in [Y.1540].  Composition of packet reordering metrics
   [RFC4737] and duplication metrics [RFC5560] are considered research
   topics at the time this memo was prepared, and are beyond the scope
   of this document.

   This memo will retain the terminology of the IPPM Framework [RFC2330]
   as much as possible, but will extend the terminology when necessary.
   It is assumed that the reader is familiar with the concepts
   introduced in [RFC2330], as they will not be repeated here.








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4.  Terminology

   This section defines the terminology applicable to the processes of
   metric composition and aggregation.

4.1.  Measurement Point

   A measurement point is the logical or physical location where packet
   observations are made.  The term "measurement point" is synonymous
   with the term "observation position" used in [RFC2330] when
   describing the notion of wire time.  A measurement point may be at
   the boundary between a host and an adjacent link (physical), or it
   may be within a host (logical) that performs measurements where the
   difference between host time and wire time is understood.

4.2.  Complete Path

   The complete path is the actual path that a packet would follow as it
   travels from the packet's Source to its Destination.  A complete path
   may span the administrative boundaries of one or more networks.

4.3.  Complete Path Metric

   The complete path metric is the Source-to-Destination metric that a
   composed metric attempts to estimate.  A complete path metric
   represents the ground-truth for a composed metric.

4.4.  Complete Time Interval

   The complete time interval is comprised of two or more contiguous
   sub-intervals, and is the interval whose performance will be
   estimated through temporal aggregation.

4.5.  Composed Metric

   A composed metric is an estimate of an actual metric describing the
   performance of a path over some time interval.  A composed metric is
   derived from other metrics by applying a deterministic process or
   function (e.g., a composition function).  The process may use metrics
   that are identical to the metric being composed, or metrics that are
   dissimilar, or some combination of both types.

4.6.  Composition Function

   A composition function is a deterministic process applied to
   individual metrics to derive another metric (such as a composed
   metric).




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4.7.  Ground Truth

   As applied here, the notion of "ground truth" is defined as the
   actual performance of a network path over some time interval.  The
   ground truth is a metric on the (unavailable) packet transfer
   information for the desired path and time interval that a composed
   metric seeks to estimate.

4.8.  Interval

   An interval refers to a span of time.

4.9.  Sub-Interval

   A sub-interval is a time interval that is included in another
   interval.

4.10.  Sub-Path

   A sub-path is a portion of the complete path where at least the
   sub-path Source and Destination hosts are constituents of the
   complete path.  We say that such a sub-path is "involved" in the
   complete path.

   Since sub-paths terminate on hosts, it is important to describe how
   sub-paths are considered to be joined.  In practice, the Source and
   Destination hosts may perform the function of measurement points.

   If the Destination and Source hosts of two adjoining paths are
   co-located and the link between them would contribute negligible
   performance, then these hosts can be considered equivalent (even if
   there is no physical link between them, this is a practical
   concession).

   If the Destination and Source hosts of two adjoining paths have a
   link between them that contributes to the complete path performance,
   then the link and hosts constitute another sub-path that is involved
   in the complete path, and should be characterized and included in the
   composed metric.

4.11.  Sub-Path Metrics

   A sub-path path metric is an element of the process to derive a
   composed metric, quantifying some aspect of the performance of a
   particular sub-path from its Source to Destination.






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5.  Description of Metric Types

   This section defines the various classes of composition.  There are
   two classes more accurately described as aggregation over time and
   space, and the third involves concatenation in space.

5.1.  Temporal Aggregation Description

   Aggregation in time is defined as the composition of metrics with the
   same type and scope obtained in different time instants or time
   windows.  For example, starting from a time series of the
   measurements of maximum and minimum one-way delay (OWD) on a certain
   network path obtained over 5-minute intervals, we obtain a time
   series measurement with a coarser resolution (60 minutes) by taking
   the maximum of 12 consecutive 5-minute maxima and the minimum of 12
   consecutive 5-minute minima.

   The main reason for doing time aggregation is to reduce the amount of
   data that has to be stored, and make the visualization/spotting of
   regular cycles and/or growing or decreasing trends easier.  Another
   useful application is to detect anomalies or abnormal changes in the
   network characteristics.

   In RFC 2330, the term "temporal composition" is introduced and
   differs from temporal aggregation in that it refers to methodologies
   to predict future metrics on the basis of past observations (of the
   same metrics), exploiting the time correlation that certain metrics
   can exhibit.  We do not consider this type of composition here.

5.2.  Spatial Aggregation Description

   Aggregation in space is defined as the combination of metrics of the
   same type and different scope, in order to estimate the overall
   performance of a larger network.  This combination may involve
   weighing the contributions of the input metrics.

   Suppose we want to compose the average one-way delay (OWD)
   experienced by flows traversing all the origin-destination (OD) pairs
   of a network (where the inputs are already metric "statistics").
   Since we wish to include the effect of the traffic matrix on the
   result, it makes sense to weight each metric according to the traffic
   carried on the corresponding OD pair:

   OWD_sum=f1*OWD_1+f2*OWD_2+...+fn*OWD_n

   where fi=load_OD_i/total_load.





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   A simple average OWD across all network OD pairs would not use the
   traffic weighting.

   Another example metric that is "aggregated in space" is the maximum
   edge-to-edge delay across a single network.  Assume that a Service
   Provider wants to advertise the maximum delay that transit traffic
   will experience while passing through his/her network.  There can be
   multiple edge-to-edge paths across a network, and the Service
   Provider chooses either to publish a list of delays (each
   corresponding to a specific edge-to-edge path), or publish a single
   maximum value.  The latter approach simplifies the publication of
   measurement information, and may be sufficient for some purposes.
   Similar operations can be provided to other metrics, e.g., "maximum
   edge-to-edge packet loss", etc.

   We suggest that space aggregation is generally useful to obtain a
   summary view of the behaviour of large network portions, or of
   coarser aggregates in general.  The metric collection time instant,
   i.e., the metric collection time window of measured metrics, is not
   considered in space aggregation.  We assume that either it is
   consistent for all the composed metrics, e.g., compose a set of
   average delays all referring to the same time window, or the time
   window of each composed metric does not affect the aggregated metric.

5.3.  Spatial Composition Description

   Concatenation in space is defined as the composition of metrics of
   same type with (ideally) different spatial scope, so that the
   resulting metric is representative of what the metric would be if
   obtained with a direct measurement over the sequence of the several
   spatial scopes.  An example is the sum of mean OWDs of adjacent edge-
   to-edge networks, where the intermediate edge points are close to
   each other or happen to be the same.  In this way, we can for example
   estimate OWD_AC starting from the knowledge of OWD_AB and OWD_BC.
   Note that there may be small gaps in measurement coverage; likewise,
   there may be small overlaps (e.g., the link where test equipment
   connects to the network).

   One key difference from examples of aggregation in space is that all
   sub-paths contribute equally to the composed metric, independent of
   the traffic load present.

5.4.  Help Metrics

   In practice, there is often the need to compute a new metric using
   one or more metrics with the same spatial and time scope.  For
   example, the metric rtt_sample_variance may be computed from two
   different metrics: the help metrics rtt_square_sum and the rtt_sum.



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   The process of using help metrics is a simple calculation and not an
   aggregation or a concatenation, and will not be investigated further
   in this memo.

5.5.  Higher-Order Composition

   Composed metrics might themselves be subject to further steps of
   composition or aggregation.  An example would be the delay of a
   maximal path obtained through the spatial composition of several
   composed delays for each complete path in the maximal path (obtained
   through spatial composition).  All requirements for first-order
   composition metrics apply to higher-order composition.

   An example using temporal aggregation: twelve 5-minute metrics are
   aggregated to estimate the performance over an hour.  The second step
   of aggregation would take 24 hourly metrics and estimate the
   performance over a day.

6.  Requirements for Composed Metrics

   The definitions for all composed metrics MUST include sections to
   treat the following topics.

   The description of each metric will clearly state:

   1. the definition (and statistic, where appropriate);

   2. the composition or aggregation relationship;

   3. the specific conjecture on which the relationship is based and
      assumptions of the statistical model of the process being
      measured, if any (see [RFC2330], Section 12);

   4. a justification of practical utility or usefulness for analysis
      using the A-frame concepts;

   5. one or more examples of how the conjecture could be incorrect and
      lead to inaccuracy;

   6. the information to be reported.

   For each metric, the applicable circumstances will be defined, in
   terms of whether the composition or aggregation:

   o  Requires homogeneity of measurement methodologies, or can allow a
      degree of flexibility (e.g., active or passive methods produce the
      "same" metric).  Also, the applicable sending streams will be
      specified, such as Poisson, Periodic, or both.



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   o  Needs information or access that will only be available within an
      operator's network, or is applicable to inter-network composition.

   o  Requires precisely synchronized measurement time intervals in all
      component metrics, or perhaps only loosely synchronized time
      intervals, or has no timing requirements at all.

   o  Requires assumption of component metric independence with regard
      to the metric being defined/composed, or other assumptions.

   o  Has known sources of inaccuracy/error and identifies the sources.

6.1.  Note on Intellectual Property Rights (IPR)

   If one or more components of the composition process are encumbered
   by Intellectual Property Rights (IPR), then the resulting composed
   metrics may be encumbered as well.  See BCP 79 [RFC3979] for IETF
   policies on IPR disclosure.

7.  Guidelines for Defining Composed Metrics

7.1.  Ground Truth: Comparison with Other IPPM Metrics

   Figure 1 illustrates the process to derive a metric using spatial
   composition, and compares the composed metric to other IPPM metrics.

   Metrics <M1, M2, M3> describe the performance of sub-paths between
   the Source and Destination of interest during time interval <T, Tf>.
   These metrics are the inputs for a composition function that produces
   a composed metric.





















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                          Sub-Path Metrics
                 ++  M1   ++ ++  M2   ++ ++  M3   ++
             Src ||.......|| ||.......|| ||.......|| Dst
                 ++   `.  ++ ++   |   ++ ++  .'   ++
                        `.        |       .-'
                          `-.     |     .'
                             `._..|.._.'
                           ,-'         `-.
                         ,'               `.
                         |   Composition   |
                         \     Function    '
                          `._           _,'
                             `--.....--'
                                  |
                 ++               |               ++
             Src ||...............................|| Dst
                 ++        Composed Metric        ++

                 ++      Complete Path Metric     ++
             Src ||...............................|| Dst
                 ++                               ++
                           Spatial Metric
                 ++   S1   ++   S2    ++    S3    ++
             Src ||........||.........||..........|| Dst
                 ++        ++         ++          ++

             Figure 1: Comparison with Other IPPM Metrics

   The composed metric is an estimate of an actual metric collected over
   the complete Source-to-Destination path.  We say that the complete
   path metric represents the ground truth for the composed metric.  In
   other words, composed metrics seek to minimize error with regard to
   the complete path metric.

   Further, we observe that a spatial metric [RFC5644] collected for
   packets traveling over the same set of sub-paths provides a basis for
   the ground truth of the individual sub-path metrics.  We note that
   mathematical operations may be necessary to isolate the performance
   of each sub-path.

   Next, we consider multiparty metrics (as defined in [RFC5644]) and
   their spatial composition.  Measurements to each of the receivers
   produce an element of the one-to-group metric.  These elements can be
   composed from sub-path metrics, and the composed metrics can be
   combined to create a composed one-to-group metric.  Figure 2
   illustrates this process.





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                             Sub-Path Metrics
                    ++  M1   ++ ++  M2   ++ ++  M3   ++
                Src ||.......|| ||.......|| ||.......||Rcvr1
                    ++       ++ ++`.     ++ ++       ++
                                    `-.
                                     M4`.++ ++  M5   ++
                                         || ||.......||Rcvr2
                                         ++ ++`.     ++
                                                `-.
                                                 M6`.++
                                                     ||Rcvr3
                                                     ++

                            One-to-Group Metric
                    ++        ++         ++          ++
                Src ||........||.........||..........||Rcvr1
                    ++        ++.        ++          ++
                                 `-.
                                    `-.  ++          ++
                                       `-||..........||Rcvr2
                                         ++.         ++
                                            `-.
                                               `-.   ++
                                                  `-.||Rcvr3
                                                     ++

               Figure 2: Composition of One-to-Group Metrics

   Here, sub-path metrics M1, M2, and M3 are combined using a
   relationship to compose the metric applicable to the Src-Rcvr1 path.
   Similarly, M1, M4, and M5 are used to compose the Src-Rcvr2 metric
   and M1, M4, and M6 compose the Src-Rcvr3 metric.

   The composed one-to-group metric would list the Src-Rcvr metrics for
   each receiver in the group:

   (Composed-Rcvr1, Composed-Rcvr2, Composed-Rcvr3)

   The ground truth for this composed metric is of course an actual one-
   to-group metric, where a single Source packet has been measured after
   traversing the complete paths to the various receivers.

7.1.1.  Ground Truth for Temporal Aggregation

   Temporal aggregation involves measurements made over sub-intervals of
   the complete time interval between the same Source and Destination.
   Therefore, the ground truth is the metric measured over the desired
   interval.



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7.1.2.  Ground Truth for Spatial Aggregation

   Spatial aggregation combines many measurements using a weighting
   function to provide the same emphasis as though the measurements were
   based on actual traffic, with inherent weights.  Therefore, the
   ground truth is the metric measured on the actual traffic instead of
   the active streams that sample the performance.

7.2.  Deviation from the Ground Truth

   A metric composition can deviate from the ground truth for several
   reasons.  Two main aspects are:

   o  The propagation of the inaccuracies of the underlying measurements
      when composing the metric.  As part of the composition function,
      errors of measurements might propagate.  Where possible, this
      analysis should be made and included with the description of each
      metric.

   o  A difference in scope.  When concatenating many active measurement
      results (from two or more sub-paths) to obtain the complete path
      metric, the actual measured path will not be identical to the
      complete path.  It is in general difficult to quantify this
      deviation with exactness, but a metric definition might identify
      guidelines for keeping the deviation as small as possible.

   The description of the metric composition MUST include a section
   identifying the deviation from the ground truth.

7.3.  Incomplete Information

   In practice, when measurements cannot be initiated on a sub-path or
   during a particular measurement interval (and perhaps the measurement
   system gives up during the test interval), then there will not be a
   value for the sub-path reported, and the result SHOULD be recorded as
   "undefined".

7.4.  Time-Varying Metrics

   The measured values of many metrics depend on time-variant factors,
   such as the level of network traffic on the Source-to-Destination
   path.  Traffic levels often exhibit diurnal (or daily) variation, but
   a 24-hour measurement interval would obscure it.  Temporal
   aggregation of hourly results to estimate the daily metric would have
   the same effect, and so the same cautions are warranted.






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   Some metrics are predominantly* time-invariant, such as the actual
   minimum one-way delay of a fixed path, and therefore temporal
   aggregation does not obscure the results as long as the path is
   stable.  However, paths do vary, and sometimes on less predictable
   time intervals than traffic variations.  (* Note: It is recognized
   that propagation delay on transmission facilities may have diurnal,
   seasonal, and even longer-term variations.)

8.  Security Considerations

   The security considerations that apply to any active measurement of
   live networks are relevant here as well.  See [RFC4656] and
   [RFC5357].

   The exchange of sub-path measurements among network providers may be
   a source of concern, and the information should be sufficiently
   anonymized to avoid revealing unnecessary operational details (e.g.,
   the network addresses of measurement devices).  However, the schema
   for measurement exchange is beyond the scope of this memo and likely
   to be covered by bilateral agreements for some time to come.

9.  Acknowledgements

   The authors would like to thank Maurizio Molina, Andy Van Maele,
   Andreas Haneman, Igor Velimirovic, Andreas Solberg, Athanassios
   Liakopulos, David Schitz, Nicolas Simar, and the Geant2 Project.  We
   also acknowledge comments and suggestions from Phil Chimento, Emile
   Stephan, Lei Liang, Stephen Wolff, Reza Fardid, Loki Jorgenson, and
   Alan Clark.

10.  References

10.1.  Normative References

   [RFC2119]   Bradner, S., "Key words for use in RFCs to Indicate
               Requirement Levels", BCP 14, RFC 2119, March 1997.

   [RFC2330]   Paxson, V., Almes, G., Mahdavi, J., and M. Mathis,
               "Framework for IP Performance Metrics", RFC 2330,
               May 1998.

   [RFC3979]   Bradner, S., Ed., "Intellectual Property Rights in IETF
               Technology", BCP 79, RFC 3979, March 2005.

   [RFC4656]   Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and
               M. Zekauskas, "A One-way Active Measurement Protocol
               (OWAMP)", RFC 4656, September 2006.




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   [RFC5357]   Hedayat, K., Krzanowski, R., Morton, A., Yum, K., and
               J. Babiarz, "A Two-Way Active Measurement Protocol
               (TWAMP)", RFC 5357, October 2008.

10.2.  Informative References

   [RFC2679]   Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way
               Delay Metric for IPPM", RFC 2679, September 1999.

   [RFC2680]   Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way
               Packet Loss Metric for IPPM", RFC 2680, September 1999.

   [RFC2681]   Almes, G., Kalidindi, S., and M. Zekauskas, "A Round-trip
               Delay Metric for IPPM", RFC 2681, September 1999.

   [RFC3393]   Demichelis, C. and P. Chimento, "IP Packet Delay
               Variation Metric for IP Performance Metrics (IPPM)",
               RFC 3393, November 2002.

   [RFC4737]   Morton, A., Ciavattone, L., Ramachandran, G., Shalunov,
               S., and J. Perser, "Packet Reordering Metrics", RFC 4737,
               November 2006.

   [RFC5481]   Morton, A. and B. Claise, "Packet Delay Variation
               Applicability Statement", RFC 5481, March 2009.

   [RFC5560]   Uijterwaal, H., "A One-Way Packet Duplication Metric",
               RFC 5560, May 2009.

   [RFC5644]   Stephan, E., Liang, L., and A. Morton, "IP Performance
               Metrics (IPPM): Spatial and Multicast", RFC 5644,
               October 2009.

   [Y.1540]    ITU-T Recommendation Y.1540, "Internet protocol data
               communication service - IP packet transfer and
               availability performance parameters", November 2007.















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Authors' Addresses

   Al Morton (editor)
   AT&T Labs
   200 Laurel Avenue South
   Middletown, NJ  07748
   USA

   Phone: +1 732 420 1571
   Fax:   +1 732 368 1192
   EMail: acmorton@att.com
   URI:   http://home.comcast.net/~acmacm/


   Steven Van den Berghe (editor)
   Alcatel-Lucent
   Copernicuslaan 50
   Antwerp  2018
   Belgium

   Phone: +32 3 240 3983
   EMail: steven.van_den_berghe@alcatel-lucent.com





























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