Network Working Group                                          A. Morton
Internet-Draft                                                 AT&T Labs
Intended status: Informational                                 B. Claise
Expires: May 21, 2008                                Cisco Systems, Inc.
                                                       November 18, 2007

             Packet Delay Variation Applicability Statement

Status of this Memo

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Copyright Notice

   Copyright (C) The IETF Trust (2007).


   Packet delay variation metrics appear in many different standards
   documents.  The metric definition in RFC 3393 has considerable
   flexibility, and it allows multiple formulations of delay variation
   through the specification of different packet selection functions.

   Although flexibility provides wide coverage and room for new ideas,
   it can make comparisons of independent implementations more

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   difficult.  Two different formulations of delay variation have come
   into wide use in the context of active measurements.  This memo
   examines a range of circumstances for active measurements of delay
   variation and their uses, and recommends which of the two forms is
   best matched to particular conditions and tasks.

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in RFC 2119 [RFC2119].

Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  4
     1.1.  Background Literature in IPPM and Elsewhere  . . . . . . .  5
     1.2.  Organization of the Memo . . . . . . . . . . . . . . . . .  6
   2.  Purpose and Scope  . . . . . . . . . . . . . . . . . . . . . .  6
   3.  Brief Descriptions of Delay Variation Uses . . . . . . . . . .  7
     3.1.  Inferring Queue Occupation on a Path . . . . . . . . . . .  7
     3.2.  Determining De-jitter Buffer Size  . . . . . . . . . . . .  7
     3.3.  Spatial Composition  . . . . . . . . . . . . . . . . . . .  9
     3.4.  Service Level Comparison . . . . . . . . . . . . . . . . .  9
     3.5.  <your favorite here> . . . . . . . . . . . . . . . . . . . 10
   4.  Formulations of IPDV and PDV . . . . . . . . . . . . . . . . . 10
     4.1.  IPDV: Inter-Packet Delay Variation . . . . . . . . . . . . 10
     4.2.  PDV: Packet Delay Variation  . . . . . . . . . . . . . . . 11
     4.3.  A "Point" about Measurement Points . . . . . . . . . . . . 11
     4.4.  Examples and Initial Comparisons . . . . . . . . . . . . . 11
   5.  Survey of Earlier Comparisons  . . . . . . . . . . . . . . . . 12
     5.1.  Demichelis' Comparison . . . . . . . . . . . . . . . . . . 13
     5.2.  Ciavattone et al.  . . . . . . . . . . . . . . . . . . . . 14
     5.3.  IPPM List Discussion from 2000 . . . . . . . . . . . . . . 15
     5.4.  Y.1540 Appendix II . . . . . . . . . . . . . . . . . . . . 17
     5.5.  Clark's ITU-T SG 12 Contribution . . . . . . . . . . . . . 17
   6.  Additional Properties and Comparisons  . . . . . . . . . . . . 17
     6.1.  Packet Loss  . . . . . . . . . . . . . . . . . . . . . . . 17
     6.2.  Path Changes . . . . . . . . . . . . . . . . . . . . . . . 18
       6.2.1.  Lossless Path Change . . . . . . . . . . . . . . . . . 19
       6.2.2.  Path Change with Loss  . . . . . . . . . . . . . . . . 20
     6.3.  Clock Stability and Error  . . . . . . . . . . . . . . . . 21
     6.4.  Spatial Composition  . . . . . . . . . . . . . . . . . . . 22
     6.5.  Reporting a Single Number (SLA)  . . . . . . . . . . . . . 22
     6.6.  Jitter in RTCP Reports . . . . . . . . . . . . . . . . . . 23
     6.7.  MAPDV2 . . . . . . . . . . . . . . . . . . . . . . . . . . 24
     6.8.  Load Balancing . . . . . . . . . . . . . . . . . . . . . . 24
   7.  Applicability of the Delay Variation Forms and

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       Recommendations  . . . . . . . . . . . . . . . . . . . . . . . 25
     7.1.  Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
       7.1.1.  Inferring Queue Occupancy  . . . . . . . . . . . . . . 25
       7.1.2.  Determining De-jitter Buffer Size  . . . . . . . . . . 25
       7.1.3.  Spatial Composition  . . . . . . . . . . . . . . . . . 26
       7.1.4.  Service Level Specification: Reporting a Single
               Number . . . . . . . . . . . . . . . . . . . . . . . . 26
     7.2.  Challenging Circumstances  . . . . . . . . . . . . . . . . 26
       7.2.1.  Clock and Storage Issues . . . . . . . . . . . . . . . 26
       7.2.2.  Frequent Path Changes  . . . . . . . . . . . . . . . . 27
       7.2.3.  Frequent Loss  . . . . . . . . . . . . . . . . . . . . 27
       7.2.4.  Load Balancing . . . . . . . . . . . . . . . . . . . . 27
     7.3.  Summary  . . . . . . . . . . . . . . . . . . . . . . . . . 27
   8.  Measurement Considerations . . . . . . . . . . . . . . . . . . 28
     8.1.  Measurement Stream Characteristics . . . . . . . . . . . . 28
     8.2.  Measurement Devices  . . . . . . . . . . . . . . . . . . . 30
     8.3.  Units of Measurement . . . . . . . . . . . . . . . . . . . 30
     8.4.  Test Duration  . . . . . . . . . . . . . . . . . . . . . . 31
     8.5.  Clock Sync Options . . . . . . . . . . . . . . . . . . . . 31
     8.6.  Distinguishing Long Delay from Loss  . . . . . . . . . . . 31
     8.7.  Accounting for Packet Reordering . . . . . . . . . . . . . 32
     8.8.  Results Representation and Reporting . . . . . . . . . . . 32
   9.  IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 32
   10. Security Considerations  . . . . . . . . . . . . . . . . . . . 33
   11. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 33
   12. Appendix on Reducing Delay Variation in Networks . . . . . . . 33
   13. Appendix on Calculating the D(min) in PDV  . . . . . . . . . . 33
   14. References . . . . . . . . . . . . . . . . . . . . . . . . . . 34
     14.1. Normative References . . . . . . . . . . . . . . . . . . . 34
     14.2. Informative References . . . . . . . . . . . . . . . . . . 35
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 36
   Intellectual Property and Copyright Statements . . . . . . . . . . 38

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1.  Introduction

   There are many ways to formulate packet delay variation metrics for
   the Internet and other packet-based networks.  The IETF itself has
   several specifications for delay variation [RFC3393], sometimes
   called jitter [RFC3550] or even inter-arrival jitter [RFC3550], and
   these have achieved wide adoption.  The International
   Telecommunication Union - Telecommunication Standardization Sector
   (ITU-T) has also recommended several delay variation metrics (called
   parameters in their terminology) [Y.1540] [G.1020], and some of these
   are widely cited and used.  Most of the standards above specify more
   than one way to quantify delay variation, so one can conclude that
   standardization efforts have tended to be inclusive rather than

   This memo uses the term "delay variation" for metrics that quantify a
   path's ability to transfer packets with consistent delay.  [RFC3393]
   and [Y.1540] both prefer this term.  Some refer to this phenomenon as
   "jitter" (and the buffers that attempt to smooth the variations as
   de-jitter buffers).  Applications of the term "jitter" are much
   broader than packet transfer performance, with "unwanted signal
   variation" as a general definition.  "Jitter" has been used to
   describe frequency or phase variations, such as data stream rate
   variations or carrier signal phase noise.  The phrase "delay
   variation" is almost self-defining and more precise, so it is
   preferred in this memo.

   Most (if not all) delay variation metrics are derived metrics, in
   that their definitions rely on another fundamental metric.  In this
   case, the fundamental metric is one-way delay, and variation is
   assessed by computing the difference between two individual one-way
   delay measurements, or a pair of singletons.  One of the delay
   singletons is taken as a reference, and the result is the variation
   with respect to the reference.  The variation is usually summarized
   for all packets in a stream using statistics.

   The industry has predominantly implemented two specific formulations
   of delay variation (for one survey of the situation,

   1.  Inter-Packet Delay Variation, IPDV, where the reference is the
       previous packet in the stream (according to sending sequence),
       and the reference changes for each packet in the stream.
       Properties of variation are coupled with packet sequence in this
       formulation.  This form was called Instantaneous Packet Delay
       Variation in early IETF contributions.

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   2.  Packet Delay Variation, PDV, where a single reference is chosen
       from the stream based on specific criteria.  The most common
       criterion for the reference is the packet with the minimum delay
       in the sample.  This term derives its name from a similar
       definition for Cell Delay Variation, an ATM performance metric.

   It is important to note that the authors of relevant standards for
   delay variation recognized there are many different users with
   varying needs, and allowed sufficient flexibility to formulate
   several metrics with different properties.  Therefore, the comparison
   is not so much between standards bodies or their specifications as it
   is between specific formulations of delay variation.  Both Inter-
   Packet Delay Variation and Packet Delay Variation are compliant with
   [RFC3393], because different packet selection functions will produce
   either form.

1.1.  Background Literature in IPPM and Elsewhere

   With more people joining the measurement community every day, it is
   possible this memo is the first from the IP Performance Metrics
   (IPPM) Working Group that the reader has consulted.  This section
   provides a brief roadmap and background on the IPPM literature, and
   the published specifications of other relevant standards

   The IPPM framework [RFC2330] provides a background for this memo and
   other IPPM RFCs.  Key terms such as singleton, sample, and statistic
   are defined there, along with methods of collecting samples (Poisson
   streams), time related issues, and the "packet of Type-P" convention.

   There are two fundamental and related metrics that can be applied to
   every packet transfer attempt: one-way loss [RFC2680] and one-way
   delay [RFC2679].  Lost and delayed packets are separated by a waiting
   time threshold.  Packets that arrive at the measurement destination
   within their waiting time have finite delay and are not lost.
   Otherwise, packets are designated lost and their delay is undefined.
   Guidance on setting the waiting time threshold may be found in
   [RFC2680] and [I-D.morton-ippm-reporting-metrics].

   Another fundamental metric is packet reordering as specified in
   [RFC4737].  The reordering metric was defined to be "orthogonal" to
   packet loss.  In other words, the gap in a packet sequence caused by
   loss does not result in reordered packets, but a re-arrangement of
   packet arrivals from their sending order constitutes reordering.

   Derived metrics are based on the fundamental metrics.  The metric of
   primary interest here is delay variation [RFC3393], a metric which is
   derived from one-way delay [RFC2680].  Another derived metric is the

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   loss patterns metric [RFC3357], which is derived from loss.

   The measured values of all metrics (both fundamental and derived)
   depend to great extent on the stream characteristics used to collect
   them.  Both Poisson streams [RFC3393] and Periodic streams [RFC3432]
   have been used with the IPDV and PDV metrics.  The choice of stream
   specifications for active measurement will depend on the purpose of
   the characterization and the constraints of the testing environment.
   Periodic streams are frequently chosen for use with IPDV and PDV,
   because the application streams that are most sensitive to delay
   variation exhibit periodicity.  Additional details that are method-
   specific are discussed the section on Measurement Considerations.

   In the ITU-T, the framework, fundamental metrics and derived metrics
   for IP performance are specified in Recommendation Y.1540 [Y.1540].
   [G.1020] defines additional delay variation metrics, analyses the
   operation of fixed and adaptive de-jitter buffers, and describes an
   example adaptive de-jitter buffer emulator.  Appendix II of [G.1050]
   describes the models for network impairments (including delay
   variation) that are part of standardized IP network emulator which
   may be useful when evaluating measurement techniques.

1.2.  Organization of the Memo

   The Purpose and Scope follows in Section 2.  We then give a summary
   of the main tasks for delay variation metrics in section 3.  Section
   4 defines the two primary forms of delay variation, and section 5
   presents summaries of four earlier comparisons.  Section 6 adds new
   comparisons to the analysis, and section 7 reviews the applicability
   and recommendations for each form of delay variation.  Section 8 then
   looks at many important delay variation measurement considerations.
   Following the IANA and Security Considerations, there are two
   Appendices.  One presents guidance on reducing delay variation in
   networks, and the other calculation of the minimum delay for the PDV

2.  Purpose and Scope

   The IPDV and PDV formulations have certain features that make them
   more suitable for one circumstance and less so for another.  The
   purpose of this memo is to compare two forms of delay variation, so
   that it will be evident which of the two is better suited for each of
   many possible uses and their related circumstances.

   The scope of this memo is limited to the two forms of delay variation
   briefly described above (Inter-Packet Delay Variation and Packet
   Delay Variation), circumstances related to active measurement, and

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   uses that are deemed relevant and worthy of inclusion here through
   IPPM Working Group consensus.

   It is entirely possible that the analysis and conclusions drawn here
   are applicable beyond the intended scope, but the reader is cautioned
   to fully appreciate the circumstances of active measurement on IP
   networks before doing so.

   The scope excludes assessment of delay variation for packets with
   undefined delay.  This is accomplished by conditioning the delay
   distribution on arrival within a reasonable waiting time based on an
   understanding of the path under test and packet lifetimes.  The
   waiting time is sometimes called the loss threshold [RFC2680]: if a
   packet arrives beyond this threshold, it may as well have been lost
   because it is no longer useful.  This is consistent with [RFC3393],
   where the Type-P-One-way-ipdv is undefined when the destination fails
   to receive one or both packets in the selected pair.  Furthermore, it
   is consistent with application performance analysis to consider only
   arriving packets, because a finite waiting time-out is a feature of
   many protocols.

3.  Brief Descriptions of Delay Variation Uses

   This section presents a set of tasks that call for delay variation
   measurements.  Here, the memo provides several answers to the
   question, "How will the results be used?" for the delay variation

3.1.  Inferring Queue Occupation on a Path

   As packets travel along the path from source to destination, they
   pass through many network elements, including a series of router
   queues.  Some types of the delay sources along the path are constant,
   such as links between two locations.  But the latency encountered in
   each queue varies, depending on the number of packets in the queue
   when a particular packet arrives.  If one assumes that at least one
   of the packets in a test stream encounters virtually empty queues all
   along the path (and the path is stable), then the additional delay
   observed on other packets can be attributed to the time spent in one
   or more queues.  Otherwise, the delay variation observed is the
   variation in queue time experienced by the test stream.

3.2.  Determining De-jitter Buffer Size

   Note - while this memo and other IPPM literature prefer the term
   delay variation, the terms "jitter buffer" and the more accurate "de-
   jitter buffer" are widely adopted names for a component of packet

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   communication systems, and they will be used here to designate that
   system component.

   Most Isochronous applications (a.k.a. real-time applications) employ
   a buffer to smooth out delay variation encountered on the path from
   source to destination.  The buffer must be big enough to accommodate
   the expected variation of delay, or packet loss will result.
   However, if the buffer is too large, then some of the desired
   spontaneity of communication will be lost and conversational dynamics
   will be affected.  Therefore, application designers need to know the
   range of delay variation they must accommodate, whether they are
   designing fixed or adaptive buffer systems.

   Network service providers also attempt to constrain delay variation
   to ensure the quality of real-time applications, and monitor this
   metric (possibly to compare with a numerical objective or Service
   Level Agreement).

   De-jitter buffer size can be expressed in units of octets of storage
   space for the packet stream, or in units of time that the packets are
   stored.  It is relatively simple to convert between octets and time
   when the buffer read rate (in octets per second) is constant:

   read_rate * storage_time = storage_octets

   Units of time are used in the discussion below.

   The objective of a de-jitter buffer is to compensate for all prior
   sources of delay variation and produce a packet stream with constant
   delay.  Thus, a packet experiencing the minimum transit delay from
   source to destination, D_min, should spend the maximum time in a de-
   jitter buffer, B_max.  The sum of D_min and B_max should equal the
   sum of the maximum transit delay (D_max) and the minimum buffer time
   (B_min).  We have

   Constant = D_min + B_max = D_max + B_min,

   after rearranging terms,

   B_max - B_min = D_max - D_min = range(B) = range(D)

   where range(B) is the range of packet buffering times, and range(D)
   is the range of packet transit delays from source to destination.

   Packets with transit delay between the max and min spend a
   complimentary time in the buffer and also see the constant delay.

   In practice, the minimum buffer time, B_min, may not be zero, and the

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   maximum transit delay, D_max may be a high percentile (99.9%-ile)
   instead of the maximum.

   Note that B_max - B_min = range(B) is the range of buffering times
   needed to compensate for delay variation.  The actual size of the
   buffer may be larger (where B_min > 0) or smaller than range(B).

   There must be a process to align the de-jitter buffer time with
   packet transit delay.  This is a process to identify the packets with
   minimum delay and schedule their play-out time so that they spend the
   maximum time in the buffer.  The error in the alignment process can
   be accounted for by a factor, A. In the equation below, the range of
   buffering times *available* to the packet stream, range(b), depends
   on buffer alignment with the actual arrival times of D_min and D_max.

   range(b) = b_max - b_min = D_max - D_min + A

   When A is positive, the de-jitter buffer applies more delay than
   necessary (where Constant = D_max+b_min+A represents one possible
   alignment).  When A is negative, there is insufficient buffer time
   available to compensate for range(D) because of mis-alignment.
   Packets with D_min may be arriving too early and encountering a full
   buffer, or packets with D_max may be arriving too late, and in either
   case the packets would be discarded.

   In summary, the range of transit delay variation is a critical factor
   in the determination of de-jitter buffer size.

3.3.  Spatial Composition

   In Spatial Composition, the tasks are similar to those described
   above, but with the additional complexity of a multiple network path
   where several sub-paths are measured separately and no source to
   destination measurements are available.  In this case, the source to
   destination performance must be estimated, using Composed Metrics as
   described in [I-D.ietf-ippm-framework-compagg] and [Y.1541].  Note
   that determining the composite delay variation is not trivial: simply
   summing the sub-path variations is not accurate.

3.4.  Service Level Comparison

   IP performance measurements are often used as the basis for
   agreements (or contracts) between service providers and their
   customers.  The measurement results must compare favorably with the
   performance levels specified in the agreement.

   Packet delay variation is usually one of the metrics specified in
   these agreements.  In principle, any formulation could be specified

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   in the Service Level Agreement (SLA).  However, the SLA is most
   useful when the measured quantities can be related to ways in which
   the communication service will be utilized by the customer, and this
   can usually be derived from one of the tasks described above.

3.5.  <your favorite here>

   Note: At the IETF-68 IPPM session, Alan Clark suggested another
   possible task for DV measurements, that of detecting and somehow
   removing the delay variation associated with a smoothing buffer used
   with a video codec.  Further work is needed to define the problem and
   to investigate the applicability of IPDV and PDV.

4.  Formulations of IPDV and PDV

   This section presents the formulations of IPDV and PDV, and provides
   some illustrative examples.  We use the basic singleton definition in
   [RFC3393] (which itself is based on [RFC2679]):

   "Type-P-One-way-ipdv is defined for two packets from Src to Dst
   selected by the selection function F, as the difference between the
   value of the Type-P-One-way-delay from Src to Dst at T2 and the value
   of the Type-P-One-Way-Delay from Src to Dst at T1."

4.1.  IPDV: Inter-Packet Delay Variation

   If we have packets in a stream consecutively numbered i = 1,2,3,...
   falling within the test interval, then IPDV(i) = D(i)-D(i-1) where
   D(i) denotes the one-way-delay of the ith packet of a stream.

   One-way delays are the difference between timestamps applied at the
   ends of the path, or the receiver time minus the transmission time.
   So D(2) = R2-T2.  With this timestamp notation, it can be shown that
   IPDV also represents the change in inter-packet spacing between
   transmission and reception:

   IPDV(2) = D(2) - D(1) = (R2-T2) - (R1-T1) = (R2-R1) - (T2-T1)

   An example selection function given in [RFC3393] is "Consecutive
   Type-P packets within the specified interval."  This is exactly the
   function needed for IPDV.  The reference packet in the pair is always
   the previous packet in the sending sequence.

   Note that IPDV can take on positive and negative values (and zero).
   One way to analyze the IPDV results is to concentrate on the positive
   excursions.  However, approach has limitations that are discussed in
   more detail below (see section 5.3).

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   The mean of all IPDV(i) for a stream is usually zero.  However, a
   slow delay change over the life of the stream, or a frequency error
   between the measurement system clocks, can result in a non-zero mean.

4.2.  PDV: Packet Delay Variation

   The name Packet Delay Variation is used in [Y.1540] and its
   predecessors, and refers to a performance parameter equivalent to the
   metric described below.

   The Selection Function for PDV requires two specific roles for the
   packets in the pair.  The first packet is any Type-P packet within
   the specified interval.  The second, or reference packet is the
   Type-P packet within the specified interval with the minimum one-way-

   Therefore, PDV(i) = D(i)-D(min) (using the nomenclature introduced in
   the IPDV section).  D(min) is the delay of the packet with the lowest
   value for delay (minimum) over the current test interval.  Values of
   PDV may be zero or positive, and quantiles of the PDV distribution
   are direct indications of delay variation.

   PDV is a version of the one-way delay distribution, shifted to the
   origin by normalizing to the minimum delay.

4.3.  A "Point" about Measurement Points

   Both IPDV and PDV are derived from the one-way delay metric.  One way
   delay requires knowledge of time at two points, e.g., the source and
   destination of an IP network path in end-to-end measurement.
   Therefore, both IPDV and PDV can be categorized as 2-point metrics
   because they are derived from one-way delay.  Specific methods of
   measurement may make assumptions or have a priori knowledge about one
   of the measurement points, but the metric definitions themselves are
   based on information collected at two measurement points.

4.4.  Examples and Initial Comparisons

   Note: This material originally presented in slides 2 and 3 of

   The Figure below gives a sample of packet delays and calculates IPDV
   and PDV values and depicts a histogram for each one.

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                       Packet #     1   2   3   4   5
                       Delay, ms   20  10  20  25  20

                       IPDV         U -10  10   5  -5

                       PDV         10   0  10  15  10

                          |                 |
                         4|                4|
                          |                 |
                         3|                3|         H
                          |                 |         H
                         2|                2|         H
                          |                 |         H
                  H   H  1|   H   H        1|H        H   H
                  H   H   |   H   H         |H        H   H
                 ---------+--------         +---------------
                -10  -5   0   5  10          0   5   10  15

                   IPDV Histogram             PDV Histogram

                     Figure 1: IPDV and PDV Comparison

   The sample of packets contains three packets with "typical" delays of
   20ms, one packet with a low delay of 10ms (the minimum of the sample)
   and one packet with 25ms delay.

   As noted above, this example illustrates that IPDV may take on
   positive and negative values, while the PDV values are greater than
   or equal to zero.  The Histograms of IPDV and PDV are quite different
   in general shape, and the ranges are different, too (IPDV range =
   20ms, PDV range = 15 ms).  Note that the IPDV histogram will change
   if the sequence of delays is modified, but the PDV histogram will
   stay the same.  PDV normalizes the one-way delay distribution to the
   minimum delay and emphasizes the variation independent from the
   sequence of delays.

5.  Survey of Earlier Comparisons

   This section summarizes previous work to compare these two forms of
   delay variation.

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5.1.  Demichelis' Comparison

   In [Demichelis], Demichelis compared the early draft versions of two
   forms of delay variation.  Although the IPDV form would eventually
   see widespread use, the ITU-T work-in-progress he cited did not
   utilize the same reference packets as PDV.  Demichelis compared IPDV
   with the alternatives of using the delay of the first packet in the
   stream and the mean delay of the stream as the PDV reference packet.
   Neither of these alternative references were used in practice, and
   they are now deprecated in favor of the minimum delay of the stream

   Active measurements of a transcontinental path (Torino to Tokyo)
   provided the data for the comparison.  The Poisson test stream had
   0.764 second average inter-packet interval, with more than 58
   thousand packets over 13.5 hours.  Among Demichelis' observations
   about IPDV are the following:

   1.  IPDV is a measure of the network's ability to preserve the
       spacing between packets.

   2.  The distribution of IPDV is usually symmetrical about the origin,
       having a balance of negative and positive values (for the most
       part).  The mean is usually zero, unless some long-term delay
       trend is present.

   3.  IPDV singletons distinguish quick delay variations (short-term,
       on the order of the interval between packets) from longer term

   4.  IPDV places reduced demands on the stability and skew of
       measurement clocks.

   He also notes these features of PDV:

   1.  The PDV distribution does not distinguish short-term variation
       from variation over the complete test interval.  (Comment: PDV
       can be determined over any sub-intervals when the singletons are

   2.  The location of the distribution is very sensitive to the delay
       of the first packet, IF this packet is used as the reference.
       This would be a new formulation that differs from the PDV
       definition in this memo (PDV references the packet with minimum
       delay, so it does not have this drawback).

   3.  The shape of the PDV distribution is identical to the delay
       distribution, but shifted by the reference delay.

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   4.  Use of a common reference over measurement intervals that are
       longer than a typical session length may indicate more PDV than
       would be experienced by streams that support such sessions.
       (Ideally, the measurement interval should be aligned with the
       session length of interest, and this influences determination of
       the reference delay, D(min).)

   5.  The PDV distribution characterizes the range of queue occupancies
       along the measurement path (assuming the path is fixed), but the
       range says nothing about how the variation took place.

   The summary metrics used in this comparison were the number of values
   exceeding a +/-50ms range around the mean, the Inverse Percentiles,
   and the Inter-Quartile Range.

5.2.  Ciavattone et al.

   In [Cia03], the authors compared IPDV and PDV (referred to as delta)
   using a periodic packet stream conforming to [RFC3432] with inter-
   packet interval of 20 ms.

   One of the comparisons between IPDV and PDV involves a laboratory
   set-up where a queue was temporarily congested by a competing packet
   burst.  The additional queuing delay was 85ms to 95ms, much larger
   than the inter-packet interval.  The first packet in the stream that
   follows the competing burst spends the longest time queued, and
   others experience less and less queuing time until the queue is

   The authors observed that PDV reflects the additional queuing time of
   the packets affected by the burst, with values of 85, 65, 45, 25, and
   5ms.  Also, it is easy to determine (by looking at the PDV range)
   that a de-jitter buffer of >85 ms would have been sufficient to
   accommodate the delay variation.  Again, the measurement interval is
   a key factor in the validity of such observations (it should have
   similar length to the session interval of interest).

   The IPDV values in the congested queue example are very different:
   85, -20, -20, -20, -20, -5ms.  Only the positive excursion of IPDV
   gives an indication of the de-jitter buffer size needed.  Although
   the variation exceeds the inter-packet interval, the extent of
   negative IPDV values is limited by that sending interval.  This
   preference for information from the positive IPDV values has prompted
   some to ignore the negative values, or to take the absolute value of
   each IPDV measurement (sacrificing key properties of IPDV in the
   process, such as its ability to distinguish delay trends).

   Note that this example illustrates a case where the IPDV distribution

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   is asymmetrical, because the delay variation range (85ms) exceeds the
   inter-packet spacing (20ms).  We see that the IPDV values 85, -20,
   -20, -20, -20, -5ms have zero mean, but the left side of the
   distribution is truncated at -20ms.

   Elsewhere, the authors considered the range as a summary statistic
   for IPDV, and the 99.9%-ile minus the minimum delay as a summary
   statistic for delay variation, or PDV.

5.3.  IPPM List Discussion from 2000

   Mike Pierce made many comments in the context of the 05 version of
   draft-ietf-ippm-ipdv.  One of his main points was that a delay
   histogram is a useful approach to quantifying variation.  Another
   point was that the time duration of evaluation is a critical aspect.

   Carlo Demichelis then mailed his comparison paper to the IPPM list,
   [Demichelis] as discussed in more detail above.

   Ruediger Geib observed that both IPDV and the delay histogram (PDV)
   are useful, and suggested that they might be applied to different
   variation time scales.  He pointed out that loss has a significant
   effect on IPDV, and encouraged that the loss information be retained
   in the arrival sequence.

   Several example delay variation scenarios were discussed, including:

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          Packet #     1   2   3   4   5   6   7   8   9  10  11
          Ex. A

          Delay, ms  100 110 120 130 140 150 140 130 120 110 100

          IPDV        U   10  10  10  10  10 -10 -10 -10 -10 -10

          PDV         0   10  20  30  40  50  40  30  20  10   0

          Ex. B
          Lost                     L

          Delay, ms  100 110 150   U 120 100 110 150 130 120 100

          IPDV        U   10  40   U   U -10  10  40 -20 -10 -20

          PDV         0   10  50   U  20   0  10  50  30  20   0

                         Figure 2: Delay Examples

   Clearly, the range of PDV values is 50 ms in both cases above, and
   this is the statistic that determines the size of a de-jitter buffer.
   The IPDV range is minimal in response to the smooth variation in
   Example A (20 ms).  However, IPDV responds to the faster variations
   in Example B (60 ms range from 40 to -20).  Here the IPDV range is
   larger than the PDV range, and over-estimates the buffer size

   A heuristic method to estimate buffer size using IPDV is to sum the
   consecutive positive or zero values as an estimate of PDV range.
   However, this is more complicated to assess than the PDV range, and
   has strong dependence on the actual sequence of IPDV values (any
   negative IPDV value stops the summation, and again causes an

   IPDV values can be viewed as the adjustments that an adaptive de-
   jitter buffer would make, IF it could make adjustments on a packet-
   by-packet basis.  However, adaptive de-jitter buffers don't make
   adjustments this frequently, so the value of this information is
   unknown.  The short-term variations may be useful to know in some
   other cases.

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5.4.  Y.1540 Appendix II

   Appendix II of [Y.1540] describes a secondary terminology for delay
   variation.  It compares IPDV, PDV (referred to as 2-point PDV), and
   1-point packet delay variation (which assumes a periodic stream and
   assesses variation against an ideal arrival schedule constructed at a
   single measurement point).  This early comparison discusses some of
   the same considerations raised in section 6 below.

5.5.  Clark's ITU-T SG 12 Contribution

   Alan Clark's contribution to ITU-T Study Group 12 in January 2003,
   provided an analysis of the root causes of delay variation and
   investigated different techniques for measurement and modeling of
   "jitter" [COM12.D98].  Clark compared a metric closely related to
   IPDV, Mean Packet-to-Packet Delay Variation, MPPDV = mean(abs(D(i)-
   D(i-1))) to the newly proposed Mean Absolute Packet Delay Variation
   (MAPDV2, see [G.1020]).  One of the tasks for this study was to
   estimate the number of packet discards in a de-jitter buffer.  Clark
   concluded that MPPDV did not track the ramp delay variation he
   associated access link congestion (similar to Figure 2, Example A
   above), but MAPDV2 did.

   Clark also briefly looked at PDV (as described in the 2002 version
   of[Y.1541]).  He concluded that if PDV was applied to a series of
   very short measurement intervals (e.g., 200ms), it could be used to
   determine the fraction of intervals with high packet discard rates.

6.  Additional Properties and Comparisons

   This section treats some of the earlier comparison areas in more
   detail, and introduces new areas for comparison.

6.1.  Packet Loss

   The measurement packet loss is of great influence for the delay
   variation results, as displayed in the figures 3 and 4 (L means Lost
   and U means undefined).  Figure 3 shows that in the extreme case of
   every other packet loss, the IPDV doesn't produce any results, while
   the PDV produces results for all arriving packets.

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                  Packet #   1  2  3  4  5  6  7  8  9 10
                  Lost          L     L     L     L     L
                  Delay, ms  3  U  5  U  4  U  3  U  4  U

                  IPDV       U  U  U  U  U  U  U  U  U  U

                  PDV        0  U  2  U  1  U  0  U  1  U

                  Figure 3: Path Loss Every Other Packet

   In case of a burst of packet loss, as displayed in figure 3, both the
   IPDV and PDV produces some results.  Note that PDV still produces
   more values than IPDV.

                  Packet #   1  2  3  4  5  6  7  8  9 10
                  Lost             L  L  L  L  L
                  Delay, ms  3  4  U  U  U  U  U  5  4  3

                  IPDV       U  1  U  U  U  U  U  U -1 -1

                  PDV        0  1  U  U  U  U  U  2  1  0

                      Figure 4: Burst of Packet Loss

   In conclusion, the PDV results are affected by the packet loss ratio.
   The IPDV results are affected by both the packet loss ratio and the
   packet loss distribution.  In the extreme case of loss of every other
   packet, IPDV doesn't provide any results.

6.2.  Path Changes

   When there is little or no stability in the network under test, then
   the devices that attempt to characterize the network are equally
   stressed, especially if the results displayed are used to make
   inferences which may not be valid.

   Sometimes the path characteristics change during a measurement
   interval.  The change may be due to link or router failure,
   administrative changes prior to maintenance (e.g., link cost change),
   or re-optimization of routing using new information.  All these
   causes are usually infrequent, and network providers take appropriate
   measures to ensure this.  Automatic restoration to a back-up path is
   seen as a desirable feature of IP networks.

   Frequent path changes and prolonged congestion with substantial
   packet loss clearly make delay variation measurements challenging.

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   Path changes are usually accompanied by a sudden, persistent increase
   or decrease in one-way-delay.  [Cia03] gives one such example.  We
   assume that a restoration path either accepts a stream of packets, or
   is not used for that particular stream (e.g., no multi-path for

   In any case, a change in the TTL (or Hop Limit) of the received
   packets indicates that the path is no longer the same.  Transient
   packet reordering may also be observed with path changes, due to use
   of non-optimal routing while updates propagate through the network
   (see [Casner] and [Cia03] )

   Many, if not all, packet streams experience packet loss in
   conjunction with a path change.  However, it is certainly possible
   that the active measurement stream does not experience loss.  This
   may be due to use of a long inter-packet sending interval with
   respect to the restoration time, and it becomes more likely as "fast
   restoration" techniques see wider deployment (e.g., [RFC4090].

   Thus, there are two main cases to consider, path changes accompanied
   by loss, and those that are lossless from the point of view of the
   active measurement stream.  The subsections below examine each of
   these cases.

6.2.1.  Lossless Path Change

   In the lossless case, a path change will typically affect only one
   IPDV singleton.  For example, the delay sequence below always
   produces IPDV=0 except in the one case where the value is 5:

   (...10, 10, 10, 10, 15, 15, 15, ...)

   produces IPDV singletons

   (..., 0, 0, 0, 5, 0, 0, ...).

   However, if the change in delay is negative and larger than the
   inter-packet sending interval, then more than one IPDV singleton may
   be affected because packet reordering is also likely to occur.

   The use of the new path and its delay variation can be quantified by
   treating the PDV distribution as bi-modal, and characterizing each
   mode separately.  This would involve declaring a new path within the
   sample, and using a new local minimum delay as the PDV reference
   delay for the sub-sample (or time interval) where the new path is

   The process of detecting a bi-modal delay distribution is made

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   difficult if the typical delay variation is larger than the delay
   change associated with the new path.  However, information on TTL (or
   Hop Limit) change or the presence of transient reordering can assist
   in an automated decision.

   The effect of path changes may also be reduced by making PDV
   measurements over short intervals (minutes, as opposed to hours).
   This way, a path change will affect one sample and its PDV values.
   Assuming that the mean or median one-way-delay changes appreciably on
   the new path, then subsequent measurements can confirm a path change
   and trigger special processing on the interval to revise the PDV

   Alternatively, if the path change is detected, by monitoring the test
   packets TTL or Hop Limit, or monitoring the change in the IGP link-
   state database, the results of measurement before and after the path
   change could be kept separated, presenting two different
   distributions.  This avoids the difficult task of determining the
   different modes of a multi-modal distribution.

6.2.2.  Path Change with Loss

   If the path change is accompanied by loss, such that the are no
   consecutive packet pairs that span the change, then no IPDV
   singletons will reflect the change.  This may or may not be
   desirable, depending on the ultimate use of the delay variation
   measurement.  The Figure 5, in which L means Lost and U means
   undefined, illustrates this case.

                    Packet #   1  2  3  4  5  6  7  8  9
                    Lost                   L  L
                    Delay, ms  3  4  3  3  U  U  8  9  8

                    IPDV       U  1 -1  0  U  U  U  1 -1

                    PDV        0  1  0  0  U  U  5  6  5

                      Figure 5: Path Change with Loss

   PDV will again produce a bimodal distribution.  But here, the
   decision process to define sub-intervals associated with each path is
   further assisted by the presence of loss, in addition to TTL,
   reordering information, and use of short measurement intervals
   consistent with the duration of user sessions.  It is reasonable to
   assume that at least loss and delay will be measured simultaneously
   with PDV and/or IPDV.

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6.3.  Clock Stability and Error

   Low cost or low complexity measurement systems may be embedded in
   communication devices that do not have access to high stability
   clocks, and time errors will almost certainly be present.  However,
   larger time-related errors (~1ms) may offer an acceptable trade-off
   for monitoring performance over a large population (the accuracy
   needed to detect problems may be much less than required for a
   scientific study, ~0.01ms for example).

   Maintaining time accuracy <<1ms has typically required access to
   dedicated time receivers at all measurement points.  Global
   positioning system (GPS) receivers have often been installed to
   support measurements.  The GPS installation conditions are fairly
   restrictive, and many prospective measurement efforts have found the
   deployment complexity and system maintenance too difficult.

   As mentioned above, [Demichelis] observed that PDV places greater
   demands on clock synchronization than for IPDV.  This observation
   deserves more discussion.  Synchronization errors have two
   components: time of day errors and clock frequency errors (resulting
   in skew).

   Both IPDV and PDV are sensitive to time-of-day errors when attempting
   to align measurement intervals at the source and destination.  Gross
   mis-alignment of the measurement intervals can lead to lost packets,
   for example if the receiver is not ready when the first test packet
   arrives.  However, both IPDV and PDV assess delay differences, so the
   error present in two one-way-delay singletons will cancel as long as
   it is constant.  So, NTP or GPS synchronization is not required to
   correct the time-of-day error in case the delay variation
   measurement, while it is required for the one-way delay measurement.

   Skew is a measure of the change in clock time over an interval w.r.t.
   a reference clock.  Both IPDV and PDV are affected by skew, but the
   error sensitivity in IPDV singletons is less because the intervals
   between consecutive packets are rather small, especially when
   compared to the overall measurement interval.  Since PDV computes the
   difference between a single reference delay (the sample minimum) and
   all other delays in the measurement interval, the constraint on skew
   error is greater to attain the same accuracy as IPDV.  Again, use of
   short PDV measurement intervals (on the order of minutes, not hours)
   provides some relief from the effects of skew error.

   If skew is present in a sample of one-way-delays, its symptom is
   typically a linear growth or decline over all the one-way-delay
   values.  As a practical matter, if the same slope appears
   consistently in the measurements, then it may be possible to fit the

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   slope and compensate for the skew in the one-way-delay measurements,
   thereby avoiding the issue in the PDV calculations that follow.  See
   [RFC3393] for additional information on compensating for skew.

   Values for IPDV may have non-zero mean over a sample when clock skew
   is present, and this tends to complicate IPDV analysis using the
   assumptions of zero mean and symmetric distribution.  A requirement
   of zero mean with IPDV raises the clock skew-derived error
   requirement to the same order as for PDV, because skew must be
   constrained over the entire measurement interval to ensure a zero
   IPDV mean.

   There is a third factor related to clock error and stability: this is
   the presence of a clock synchronization protocol (e.g., NTP) and the
   time adjustment operations that result.  When a time error is
   detected (typically on the order of a few milliseconds), the host
   clock frequency is continuously adjusted to reduce the time error.
   If these adjustments take place during a measurement interval, they
   may appear as delay variation when none was present, and therefore
   are a source of error (regardless of the DV form considered).

6.4.  Spatial Composition

   ITU-T Recommendation [Y.1541] gives a provisional method to compose a
   PDV metric using PDV measurement results from two or more sub-paths.
   Additional methods are considered in

   PDV has a clear advantage at this time, since there is no validated
   method to compose an IPDV metric.  In addition, IPDV results depend
   greatly on the exact sequence of packets and may not lend themselves
   easily to the composition problem.

6.5.  Reporting a Single Number (SLA)

   Despite the risk of over-summarization, measurements must often be
   displayed for easy consumption.  If the right summary report is
   prepared, then the "dashboard" view correctly indicates whether there
   is something different and worth investigating further, or that the
   status has not changed.  The dashboard model restricts every
   instrument display to a single number.  The packet network dashboard
   could have different instruments for loss, delay, delay variation,
   reordering, etc., and each must be summarized as a single number for
   each measurement interval.  The single number summary statistic is a
   key component of SLAs, where a threshold on that number must be met
   x% of the time.

   The simplicity of the PDV distribution lends itself to this

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   summarization process (including use of the percentiles, median or
   mean).  An SLA of the form "no more than x% of packets in a
   measurement interval shall have PDV >= y ms, for no less than z% of
   time" is relatively straightforward to specify and implement.
   [Y.1541] introduced the notion of a pseudo-range when setting an
   objective for the 99.9%-ile of PDV.  The conventional range (max-min)
   was avoided for several reasons, including stability of the maximum
   delay.  The 99.9%-ile of PDV is helpful to performance planners
   (seeking to meet some user-to-user objective for delay) and in design
   of de-jitter buffer sizes, even those with adaptive capabilities.

   IPDV does not lend itself to summarization so easily.  The mean IPDV
   is typically zero.  As the IPDV distribution will have two tails
   (positive and negative) the range or pseudo-range would not match the
   needed de-jitter buffer size.  Additional complexity may be
   introduced when the variation exceeds the inter-packet sending
   interval, as discussed above.  Should the Inter-Quartile Range be
   used?  Should the singletons beyond some threshold be counted (e.g.,
   mean +/- 50ms)?  A strong rationale for one of these summary
   statistics has yet to emerge.

   When summarizing IPDV, some prefer the simplicity of the single-sided
   distribution created by taking the absolute value of each singleton
   result, abs(D(i)-D(i-1)).  This approach sacrifices the two-sided
   inter-arrival spread information in the distribution.  It also makes
   the evaluation using percentiles more confusing, because a single
   late packet that exceeds the variation threshold will cause two
   singleton measurement pairs to fail the criteria (one positive, the
   other negative converted to positive).  The single-sided PDV
   distribution is an advantage in this category.

6.6.  Jitter in RTCP Reports

   [RFC3550] gives the calculation of the inter-arrival Jitter field for
   the RTCP report, with a sample implementation in an Appendix.

   The RTCP Jitter value can be calculated using IPDV singletons.  If
   there is packet reordering, as defined in [RFC4737], then estimates
   of Jitter based on IPDV may vary slightly, because [RFC3550]
   specifies the use of receive packet order.

   Just as there is no simple way to convert PDV singletons to IPDV
   singletons without returning to the original sample of delay
   singletons, there is no clear relationship between PDV and [RFC3550]

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6.7.  MAPDV2

   MAPDV2 stands for Mean Absolute Packet Delay Variation (version) 2,
   and is specified in [G.1020].  The MAPDV2 algorithm computes a
   smoothed running estimate of the mean delay using the one-way delays
   of 16 previous packets.  It compares the current one-way-delay to the
   estimated mean, separately computes the means of positive and
   negative deviations, and sums these deviation means to produce
   MAPVDV2.  In effect, there is a MAPDV2 singleton for every arriving
   packet, so further summarization is usually warranted.

   Neither IPDV or PDV forms assist in the computation of MAPDV2.

6.8.  Load Balancing

   Network traffic load balancing is a process to divide packet traffic
   in order to provide a more even distribution over two or more equally
   viable paths.  The paths chosen are based on the IGP cost metrics,
   while the delay depends on the path's physical layout.  Usually, the
   balancing process is performed on a per-flow basis to avoid delay
   variation experienced when packets traverse different physical paths.

   If the sample includes test packets with different characteristics
   such as IP addresses/ports, there could be multi-modal delay
   distributions present.  The PDV form makes the identification of
   multiple modes possible.  IPDV may also reveal that multiple paths
   are in use with a mixed flow sample, but the different delay modes
   are not easily divided and analyzed separately.

   Should the delay singletons using multiple addresses/ports be
   combined in the same sample?  Should we characterize each mode
   separately?  (This question also applies to the Path Change case.)
   It depends on the task to be addressed by the measurement.

   For the task of de-jitter buffer sizing or assessing queue
   occupation, the modes should be characterized separately because
   flows will experience only one mode on a stable path.  Use of a
   single flow description (address/port combination) in each sample
   simplifies this analysis.  Multiple modes may be identified by
   collecting samples with different flow attributes, and
   characterization of multiple paths can proceed with comparison of the
   delay distributions from each sample.

   For the task of capacity planning and routing optimization,
   characterizing the modes separately could offer an advantage.
   Network wide capacity planning (as opposed to link capacity planning)
   takes as input the core traffic matrix, which corresponds to a matrix
   of traffic transferred from every source to every destination in the

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   network.  Applying the core traffic matrix along with the routing
   information (typically the link state database of a routing protocol)
   in a capacity planning tool offers the possibility to visualize the
   paths where the traffic flows and to optimize the routing based on
   the link utilization.  In the case where equal cost multiple paths
   (ECMP) are used, the traffic will be load balanced onto multiple
   paths.  If each mode of the IP delay multi-modal distribution can be
   associated with a specific path, the delay performance offers an
   extra optimization parameter, i.e. the routing optimization based on
   the IP delay variation metric.  As an example, the load balancing
   across ECMPs could be suppressed so that the VoIP calls would only be
   routed via the path with the lower IP delay variation.  Clearly, any
   modifications can result in new delay performance measurements, so
   there must be a verification step to ensure the desired outcome.

7.  Applicability of the Delay Variation Forms and Recommendations

   Based on the comparisons of IPDV and PDV presented above, this
   section matches the attributes of each form with the tasks described
   earlier.  We discuss the more general circumstances first.

7.1.  Uses

7.1.1.  Inferring Queue Occupancy

   The PDV distribution is anchored at the minimum delay observed in the
   measurement interval.  When the sample minimum coincides with the
   true minimum delay of the path, then the PDV distribution is
   equivalent to the queuing time distribution experienced by the test
   stream.  If the minimum delay is not the true minimum, then the PDV
   distribution captures the variation in queuing time and some
   additional amount of queuing time is experienced, but unknown.  One
   can summarize the PDV distribution with the mean, median, and other

   IPDV can capture the difference in queuing time from one packet to
   the next, but this is a different distribution from the queue
   occupancy revealed by PDV.

7.1.2.  Determining De-jitter Buffer Size

   This task is complimentary to the problem of inferring queue
   occupancy through measurement.  Again, use of the sample minimum as
   the reference delay for PDV yields a distribution that is very
   relevant to de-jitter buffer size.  This is because the minimum delay
   is an alignment point for the smoothing operation of de-jitter
   buffers.  A de-jitter buffer that is ideally aligned with the delay

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   variation adds zero buffer time to packets with the longest
   accommodated network delay (any packets with longer delays are
   discarded).  Thus, a packet experiencing minimum network delay should
   be aligned to wait the maximum length of the de-jitter buffer.  With
   this alignment, the stream is smoothed with no unnecessary delay
   added.  [G.1020] illustrates the ideal relationship between network
   delay variation and buffer time.

   The PDV distribution is also useful for this task, but different
   statistics are preferred.  The range (max-min) or the 99.9%-ile of
   PDV (pseudo-range) are closely related to the buffer size needed to
   accommodate the observed network delay variation.

   In some cases, the positive excursions (or series of positive
   excursions) of IPDV may help to approximate the de-jitter buffer
   size, but there is no guarantee that a good buffer estimate will
   emerge, especially when the delay varies as a positive trend over
   several test packets.

7.1.3.  Spatial Composition

   PDV has a clear advantage at this time, since there is no validated
   method to compose an IPDV metric.

7.1.4.  Service Level Specification: Reporting a Single Number

   The one-sided PDV distribution can be constrained with a single
   statistic, such as an upper percentile, so it is preferred.  The IPDV
   distribution is two-sided, usually has zero mean, and no universal
   summary statistic that relates to a physical quantity has emerged in
   years of experience.

7.2.  Challenging Circumstances

   Note that measurement of delay variation may not be the primary
   concern under unstable and unreliable circumstances.

7.2.1.  Clock and Storage Issues

   When appreciable skew is present between measurement system clocks,
   then IPDV has an advantage because PDV would require processing over
   the entire sample to remove the skew error.  However, significant
   skew can invalidate IPDV analysis assumptions, such as the zero mean
   and symmetric distribution characteristics.  Small skew may well be
   within the error tolerance, and both PDV and IPDV results will be
   usable.  There may be a portion of the skew, measurement interval,
   and required accuracy 3-D space where IPDV has an advantage,
   depending on the specific measurement specifications.

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   Neither form of delay variation is more suited than the other to on-
   the-fly summarization without memory, and this may be one of the
   reasons that [RFC3550] RTCP Jitter and MAPDV2 in [G.1020] have
   attained deployment in low-cost systems.

7.2.2.  Frequent Path Changes

   If the network under test exhibits frequent path changes, on the
   order of several new routes per minute, then IPDV appears to isolate
   the delay variation on each path from the transient effect of path
   change (especially if there is packet loss at the time of path
   change).  However, if one intends to use IPDV to indicate path
   changes, it cannot do this when the change is accompanied by loss.
   It is possible to make meaningful PDV measurements when paths are
   unstable, but great importance would be placed on the algorithms that
   infer path change and attempt to divide the sample on path change

   When path changes are frequent and cause packet loss, delay variation
   is probably less important than the loss episodes and attention
   should be turned to the loss metric instead.

7.2.3.  Frequent Loss

   If the network under test exhibits frequent loss, then PDV may
   produce a larger set of singletons for the sample than IPDV.  This is
   due to IPDV requiring consecutive packet arrivals to assess delay
   variation, compared to PDV where any packet arrival is useful.  The
   worst case is when no consecutive packets arrive, and the entire IPDV
   sample would be undefined.  PDV would successfully produce a sample
   based on the arriving packets.

7.2.4.  Load Balancing

   PDV distributions offer the most straightforward way to identify that
   a sample of packets have traversed multiple paths.  The tasks of de-
   jitter buffer sizing or assessing queue occupation with PDV should be
   use a sample with a single flow because flows will experience only
   one mode on a stable path, and it simplifies the analysis.

7.3.  Summary

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   | Comparison    | PDV                   | IPDV                      |
   | Area          |                       |                           |
   | Challenging   | Less sensitive to     | Preferred when path       |
   | Circumstances | packet loss, and      | changes are frequent or   |
   |               | simplifies analysis   | when measurement clocks   |
   |               | when Load balancing   | exhibit some skew         |
   |               | or multiple paths are |                           |
   |               | present               |                           |
   | Spatial       | All validated methods | Has sensitivity to        |
   | Composition   | use this form         | sequence and spacing      |
   | of DV metric  |                       | changes, which tend to    |
   |               |                       | break the segment IID     |
   |               |                       | requirement               |
   | Determine     | "Pseudo-range"        | No reliable relationship, |
   | De-Jitter     | reveals this property | but some heuristics       |
   | Buffer Size   | by anchoring the      |                           |
   | Required      | distribution at the   |                           |
   |               | minimum delay         |                           |
   | Estimate of   | Distribution has      | No reliable relationship  |
   | Queuing Time  | one-to-one            |                           |
   | and Variation | relationship on a     |                           |
   |               | stable path,          |                           |
   |               | especially when       |                           |
   |               | sample min = true min |                           |
   | Specification | One constraint needed | Distribution is           |
   | Simplicity:   | for single-sided      | two-sided, usually has    |
   | Single Number | distribution, and     | zero mean, and no         |
   | SLS           | easily related to     | universal summary         |
   |               | quantities above      | statistic that relates to |
   |               |                       | a physical quantity       |

                          Summary of Comparisons

8.  Measurement Considerations

   TO DO: Add info comparing methodological approximations for each
   form, including on-the-fly statistics, memory requirements,
   implications on the reference value (D(min)), quantiles not available
   as a running measure, (possibly in a new subsection)

8.1.  Measurement Stream Characteristics

   As stated in the background section, there is a strong dependency
   between the active measurement stream characteristics and the

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   results.  The IPPM literature includes two primary methods for
   collecting samples: Poisson sampling described in [RFC2330], and
   Periodic sampling in[RFC3432].  The Poisson method was intended to
   collect an unbiased sample of performance, while the Periodic method
   addresses a "known bias of interest".  Periodic streams are required
   to have random start times and limited stream duration, in order to
   avoid unwanted synchronization with some other periodic process, or
   cause congestion-aware senders to synchronize with the stream and
   produce atypical results.  The random start time should be different
   for each new stream.

   It is worth noting that [RFC3393] was developed in parallel with
   [RFC3432].  As a result, all the stream metrics defined in [RFC3393]
   specify the Poisson sampling method.

   Periodic sampling is frequently used in measurements of delay
   variation.  Several factors foster this choice:

   1.  Many application streams that are sensitive to delay variation
       also exhibit periodicity, and so exemplify the bias of interest.
       If the application has a constant packet spacing, this constant
       spacing can be the inter-packet gap for the test stream.  VoIP
       streams often use 20ms spacing, so this is an obvious choice for
       an Active stream.  This applies to both IPDV and PDV forms.

   2.  The spacing between packets in the stream will influence whether
       the stream experiences short-range dependency, or only long-range
       dependency, as investigated in [Li.Mills].  The packet spacing
       also influences the IPDV distribution and the stream's
       sensitivity to reordering.  For example, with a 20 ms spacing the
       IPDV distribution cannot go below -20ms without packet

   3.  The measurement process may make several simplifying assumptions
       when the send spacing and send rate are constant.  For example,
       the inter-arrival times at the destination can be compared with
       an ideal sending schedule, and allowing a one-point measurement
       of delay variation (described in [Y.1540]) that approximates the
       IPDV form.  Simplified methods that approximate PDV are possible
       as well (some are discussed in Appendix II of [Y.1541]).

   4.  Analysis of truncated, or non-symmetrical IPDV distributions is
       simplified.  Delay variations in excess of the periodic sending
       interval can cause multiple singleton values at the negative
       limit of the packet spacing (see section 5.2 and [Cia03]).  Only
       packet reordering can cause the negative spacing limit to be

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   Despite the emphasis on inter-packet delay differences with IPDV,
   both Poisson [Demichelis] and Periodic [Li.Mills] streams have been
   used, and these references illustrate the different analyses that are

   The advantages of using a Poisson distribution are discussed in
   [RFC2330].  The main properties are to avoid predicting the sample
   times, avoid synchronization with periodic events that are present in
   networks, and avoid inducing synchronization with congestion-aware
   senders.  When a Poisson stream is used with IPDV, the distribution
   will reflect inter-packet delay variation on many different time
   scales (or packet spacings).  The unbiased Poisson sampling brings a
   new layer of complexity in the analysis of IPDV distributions.

8.2.  Measurement Devices

   One key aspect of measurement devices is their ability to store
   singleton measurements.  This feature usually is closely related to
   local calculation capabilities.  For example, an embedded measurement
   device with limited storage will like provide only a few statistics
   on the delay variation distribution, while dedicated measurement
   systems store all the singletons and allow detailed analysis (later
   calculation of either form of delay variation is possible with the
   original singletons).

   Therefore, systems with limited storage must choose their metrics and
   summary statistics in advance.  If both IPDV and PDV statistics are
   desired, the supporting information must be collected as packets
   arrive.  For example, the PDV range and high percentiles can be
   determined later if the minimum and several of the largest delays are
   stored while the measurement is in-progress.

8.3.  Units of Measurement

   Both IPDV and PDV can be summarized as a range in milliseconds.

   With IPDV, it is interesting to report on a positive percentile, and
   an inter-quantile range is appropriate to reflect both positive and
   negative tails (e.g., 5% to 95%).  If the IPDV distribution is
   symmetric around a mean of zero, then it is sufficient to report on
   the positive side of the distribution.

   With PDV, it is sufficient to specify the upper percentile (e.g.,

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8.4.  Test Duration

   At several points in this memo, we have recommended use of test
   intervals on the order of minutes.  In their paper examining the
   stability of Internet path properties[Zhang.Duff], Zhang et al.
   concluded that consistency was present on the order of minutes for
   the performance metrics considered (loss, delay, and throughput) for
   the paths they measured.

   The topic of temporal aggregation of performance measured in small
   intervals to estimate some larger interval is described in the Metric
   Composition Framework [I-D.ietf-ippm-framework-compagg].

   The primary recommendation here is to test using durations that are
   similar in length to the session time of interest.  This applies to
   both IPDV and PDV, but is possibly more relevant for PDV since the
   duration determines how often the D_min will be determined, and the
   size of the associated sample.

8.5.  Clock Sync Options

   As with one-way delay measurements, local clock synchronization is an
   important matter for delay variation measurements.

   There are several options available:

   1.  Global Positioning System receivers

   2.  In some parts of the world, Cellular Code Division Multiple
       Access (CDMA) systems distribute timing signals that are derived
       from GPS and traceable to UTC.

   3.  Network Time Protocol [RFC1305] is a convenient choice in many
       cases, but usually offers lower accuracy than the options above.

8.6.  Distinguishing Long Delay from Loss

   Lost and delayed packets are separated by a waiting time threshold.
   Packets that arrive at the measurement destination within their
   waiting time have finite delay and are not lost.  Otherwise, packets
   are designated lost and their delay is undefined.  Guidance on
   setting the waiting time threshold may be found in [RFC2680] and

   In essence, [I-D.morton-ippm-reporting-metrics] suggests to use a
   long waiting time to serve network characterization and revise
   results for specific application delay thresholds as needed.

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8.7.  Accounting for Packet Reordering

   Packet reordering, defined in [RFC4737], is essentially an extreme
   form of delay variation where the packet stream arrival order differs
   from the sending order.

   PDV results are not sensitive to packet arrival order, and are not
   affected by reordering other than to reflect the more extreme

   IPDV results will change if reordering is present because they are
   sensitive to the sequence of delays of arriving packets.  The main
   example of this sensitivity is in the truncation of the negative tail
   of the distribution.

   o  When there is no reordering, the negative tail is limited by the
      sending time spacing between packets.

   o  If reordering occurs, the negative tail can take on any value (in

   In general, measurement systems should have the capability to detect
   when sequence has changed.  If IPDV measurements are made without
   regard to packet arrival order, the IPDV will be under-reported when
   reordering occurs.

8.8.  Results Representation and Reporting

   All of the references that discuss or define delay variation suggest
   ways to represent or report the results, and interested readers
   should review the various possibilities.

   For example, [I-D.morton-ippm-reporting-metrics] suggests to report a
   pseudo range of delay variation based on calculating the difference
   between a high percentile of delay and the minimum delay.  The 99.9%-
   ile minus the minimum will give a value that can be compared with
   objectives in [Y.1541].

9.  IANA Considerations

   This document makes no request of IANA.

   Note to RFC Editor: this section may be removed on publication as an

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10.  Security Considerations

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

11.  Acknowledgements

   The authors would like to thank Phil Chimento for his suggestion to
   employ the convention of conditional distributions for Delay to deal
   with packet loss, and his encouragement to "write the memo" after
   hearing the talk on this topic at IETF-65.  We also acknowledge
   constructive comments from Alan Clark, Loki Jorgenson, Carsten
   Schmoll, and Robert Holley.

12.  Appendix on Reducing Delay Variation in Networks

   This text is both preliminary and generic but we want to explain the
   basic troubleshooting.

   If there is a DV problem, it may be because:

   1. there is congestion.  Find where the bottleneck is, and increase
   the buffer Alternatively, increase the bandwidth Alternatively,
   remove some applications from that class of service

   2. there is a variability of the traffic Discover that traffic, then
   change/apply QoS (for example, rate-limiting)

13.  Appendix on Calculating the D(min) in PDV

   Practitioners have raised questions several questions that this
   section intends to answer:

   - how is this D_min calculated?  Is it DV(99%) as mentioned in

   - do we need to keep all the values from the interval, then take the
   minimum?  Or do we keep the minimum from previous intervals?

   The value of D_min used as the reference delay for PDV calculations
   is simply the minimum delay of all packets in the current sample.
   The usual single value summary of the PDV distribution is D_99.9%-ile
   minus D_min.

   It may be appropriate to segregate sub-sets and revise the minimum

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   value during a sample.  For example, if it can be determined with
   certainty that the path has changed by monitoring the Time to Live or
   Hop Count of arriving packets, this may be sufficient justification
   to reset the minimum for packets on the new path.  There is also a
   simpler approach to solving this problem: use samples collected over
   short evaluation intervals (on the order of minutes).  Intervals with
   path changes may be more interesting from the loss or one-way delay
   perspective (possibly failing to meet one or more SLAs), and it may
   not be necessary to conduct delay variation analysis.  Short
   evaluation intervals are preferred for measurements that serve as a
   basis for troubleshooting, since the results are available to report
   soon after collection.

   It is not necessary to store all delay values in a sample when
   storage is a major concern.  D_min can be found by comparing each new
   singleton value with the current value and replacing it when
   required.  In a sample with 5000 packets, evaluation of the 99.9%-ile
   can also be achieved with limited storage.  One method calls for
   storing the top 50 delay singletons and revising the top value list
   each time 50 more packets arrive.

14.  References

14.1.  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.

   [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.

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

   [RFC3432]  Raisanen, V., Grotefeld, G., and A. Morton, "Network
              performance measurement with periodic streams", RFC 3432,
              November 2002.

   [RFC3550]  Schulzrinne, H., Casner, S., Frederick, R., and V.

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              Jacobson, "RTP: A Transport Protocol for Real-Time
              Applications", STD 64, RFC 3550, July 2003.

   [RFC4090]  Pan, P., Swallow, G., and A. Atlas, "Fast Reroute
              Extensions to RSVP-TE for LSP Tunnels", RFC 4090,
              May 2005.

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

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

14.2.  Informative References

              Clark, Alan., "ITU-T Delayed Contribution COM 12 - D98,
              "Analysis, measurement and modelling of Jitter"",
              January 2003.

   [Casner]   "A Fine-Grained View of High Performance Networking, NANOG
              22 Conf.;", May
              20-22 2001.

   [Cia03]    "Standardized Active Measurements on a Tier 1 IP Backbone,
              IEEE Communications Mag., pp 90-97.", June 2003.

              01-pap02.doc, "Packet Delay Variation Comparison between
              ITU-T and IETF Draft Definitions", November 2000.

   [G.1020]   ITU-T Recommendation G.1020, ""Performance parameter
              definitions for the quality of speech and other voiceband
              applications utilizing IP networks"", 2006.

   [G.1050]   ITU-T Recommendation G.1050, ""Network model for
              evaluating multimedia transmission performance over
              Internet Protocol"", November 2005.

              Morton, A., "Framework for Metric Composition",
              draft-ietf-ippm-framework-compagg-05 (work in progress),
              November 2007.


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              Morton, A. and E. Stephan, "Spatial Composition of
              Metrics", draft-ietf-ippm-spatial-composition-05 (work in
              progress), November 2007.

              Morton, A., Ramachandran, G., and G. Maguluri, "Reporting
              Metrics: Different Points of View",
              draft-morton-ippm-reporting-metrics-03 (work in progress),
              November 2007.

              Presentation at IPPM, IETF-64, "Jitter Definitions: What
              is What?", November 2005.

              Li, Quong. and David. Mills, ""The Implications of Short-
              Range Dependency on Delay Variation Measurement", Second
              IEEE Symposium on Network Computing and Applications",

              Morton, A., ""A Brief Jitter Metrics Comparison, and not
              the last word, by any means...", Slide Presentation at
              IETF-65, IPPM Session,", March 2006.

   [RFC1305]  Mills, D., "Network Time Protocol (Version 3)
              Specification, Implementation", RFC 1305, March 1992.

   [RFC3357]  Koodli, R. and R. Ravikanth, "One-way Loss Pattern Sample
              Metrics", RFC 3357, August 2002.

   [Y.1540]   ITU-T Recommendation Y.1540, "Internet protocol data
              communication service - IP packet transfer and
              availability performance parameters", December  2002.

   [Y.1541]   ITU-T Recommendation Y.1540, "Network Performance
              Objectives for IP-Based Services", February  2006.

              Zhang, Yin., Duffield, Nick., Paxson, Vern., and Scott.
              Shenker, ""On the Constancy of Internet Path Properties",
              Proceedings of ACM SIGCOMM Internet Measurement
              Workshop,", November 2001.

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Authors' Addresses

   Al Morton
   AT&T Labs
   200 Laurel Avenue South
   Middletown,, NJ  07748

   Phone: +1 732 420 1571
   Fax:   +1 732 368 1192

   Benoit Claise
   Cisco Systems, Inc.
   De Kleetlaan 6a b1
   Diegem,   1831

   Phone: +32 2 704 5622

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Full Copyright Statement

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