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Advanced Stream and Sampling Framework for IPPM

The information below is for an old version of the document.
Document Type
This is an older version of an Internet-Draft that was ultimately published as RFC 7312.
Authors Joachim Fabini , Al Morton
Last updated 2014-05-15 (Latest revision 2014-04-16)
Replaces draft-morton-ippm-2330-update
RFC stream Internet Engineering Task Force (IETF)
Additional resources Mailing list discussion
Stream WG state Submitted to IESG for Publication
Document shepherd Bill Cerveny
Shepherd write-up Show Last changed 2014-04-21
IESG IESG state Became RFC 7312 (Informational)
Consensus boilerplate Yes
Telechat date (None)
Responsible AD Spencer Dawkins
Send notices to,
IANA IANA review state IANA OK - No Actions Needed
Network Working Group                                          J. Fabini
Internet-Draft                           Vienna University of Technology
Updates: 2330 (if approved)                                    A. Morton
Intended status: Informational                                 AT&T Labs
Expires: October 18, 2014                                 April 16, 2014

            Advanced Stream and Sampling Framework for IPPM


   To obtain repeatable results in modern networks, test descriptions
   need an expanded stream parameter framework that also augments
   aspects specified as Type-P for test packets.  This memo updates the
   IP Performance Metrics (IPPM) Framework RFC 2330 with advanced
   considerations for measurement methodology and testing.  The existing
   framework mostly assumes deterministic connectivity, and that a
   single test stream will represent the characteristics of the path
   when it is aggregated with other flows.  Networks have evolved and
   test stream descriptions must evolve with them, otherwise unexpected
   network features may dominate the measured performance.  This memo
   describes new stream parameters for both network characterization and
   support of application design using IPPM metrics.

Requirements Language

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

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on October 18, 2014.

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Copyright Notice

   Copyright (c) 2014 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   ( in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     1.1.  Definition: Reactive Path Behavior  . . . . . . . . . . .   3
   2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . .   4
   3.  New or Revised Stream Parameters  . . . . . . . . . . . . . .   5
     3.1.  Test Packet Type-P  . . . . . . . . . . . . . . . . . . .   6
       3.1.1.  Multiple Test Packet Lengths  . . . . . . . . . . . .   6
       3.1.2.  Test Packet Payload Content Optimization  . . . . . .   7
     3.2.  Packet History  . . . . . . . . . . . . . . . . . . . . .   7
     3.3.  Access Technology Change  . . . . . . . . . . . . . . . .   8
     3.4.  Time-Slotted Randomness Cancellation  . . . . . . . . . .   8
   4.  Quality of Metrics and Methodologies  . . . . . . . . . . . .   9
     4.1.  Repeatability . . . . . . . . . . . . . . . . . . . . . .  10
     4.2.  Continuity  . . . . . . . . . . . . . . . . . . . . . . .  11
     4.3.  Actionable  . . . . . . . . . . . . . . . . . . . . . . .  11
     4.4.  Conservative  . . . . . . . . . . . . . . . . . . . . . .  12
     4.5.  Spatial and Temporal Composition  . . . . . . . . . . . .  12
     4.6.  Poisson Sampling  . . . . . . . . . . . . . . . . . . . .  13
   5.  Conclusions . . . . . . . . . . . . . . . . . . . . . . . . .  13
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .  13
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  13
   8.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  13
   9.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  13
     9.1.  Normative References  . . . . . . . . . . . . . . . . . .  14
     9.2.  Informative References  . . . . . . . . . . . . . . . . .  14
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  15

1.  Introduction

   The IETF IP Performance Metrics (IPPM) working group first created a
   framework for metric development in [RFC2330].  This framework has

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   stood the test of time and enabled development of many fundamental
   metrics, while only being updated once in a specific area [RFC5835].

   The IPPM framework [RFC2330] generally relies on several assumptions,
   one of which is not explicitly stated but assumed: lightly loaded
   paths conform to the linear "delay = packet size / capacity"
   equation, being state/history-less (with some exceptions, firewalls
   are mentioned).  However, this does not hold true for many modern
   network technologies, such as reactive paths (those with demand-
   driven resource allocation) and links with time-slotted operation.
   Per-flow state can be observed on test packet streams, and such
   treatment will influence network characterization if it is not taken
   into account.  Flow history will also affect the performance of
   applications and be perceived by their users.

   Moreover, Sections 4 and 6.2 of [RFC2330] explicitly recommend
   repeatable measurement metrics and methodologies.  Measurements in
   today's access networks illustrate that methodological guidelines of
   [RFC2330] must be extended to capture the reactive nature of these
   networks.  Although the proposed extensions can support methodologies
   to fulfill the continuity requirement stated in section 6.2 of
   [RFC2330], there is no guarantee.  Practical measurements confirm
   that some link types exhibit distinct responses to repeated
   measurements with identical stimulus, i.e., identical traffic
   patterns.  If feasible, appropriate fine-tuning of measurement
   traffic patterns can improve measurement continuity and repeatability
   for these link types as shown in [IBD].

   This memo updates the IP Performance Metrics (IPPM) Framework
   [RFC2330] with advanced considerations for measurement methodology
   and testing.

   We stress that this update of [RFC2330] does not invalidate or
   require changes to the analytic metric definitions prepared in the
   IPPM working group to date.  Rather, it adds considerations for
   active measurement methodologies and expands the importance of
   existing conventions and notions in [RFC2330], such as "packets of

   Among the evolutionary networking changes is a phenomenon we call
   "reactive behavior", defined below.

1.1.  Definition: Reactive Path Behavior

   Reactive path behavior will be observable by the test packet stream
   as a repeatable phenomenon where packet transfer performance
   characteristics *change* according to prior observations of the
   packet flow of interest (at the reactive host or link).  Therefore,

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   reactive path behavior is nominally deterministic with respect to the
   flow of interest.  Other flows or traffic load conditions may result
   in additional performance-affecting reactions, but these are external
   to the characteristics of the flow of interest.

   In practice, a sender may not have absolute control of the ingress
   packet stream characteristics at a reactive host or link, but this
   does not change the deterministic reactions present there.  If we
   measure a path, the arrival characteristics at the reactive host/link
   are determined by the sending characteristics and the transfer
   characteristics of intervening hosts and links.  Identical traffic
   patterns at the sending host might generate distinct patterns at the
   reactive host's/link's input due to impairments in the intermediate
   subpath.  The reactive host/link is expected to provide deterministic
   response on identical input patterns.

   Other than the size of the payload at the layer of interest and the
   header itself, packet content does not influence the measurement.
   Reactive behavior at the IP layer is not influenced by the TCP ports
   in use, for example.  Therefore, the indication of reactive behavior
   must include the layer at which measurements are instituted.

   Examples include links with Active/In-active state detectors, and
   hosts or links that revise their traffic serving and forwarding rates
   (up or down) based on packet arrival history.

   Although difficult to handle from a measurement point of view,
   reactive paths entities are usually designed to improve overall
   network performance and user experience, for example by making
   capacity available to an active user.  Reactive behavior may be an
   artifact of solutions to allocate scarce resources according to the
   demands of users, thus it is an important problem to solve for
   measurement and other disciplines, such as application design.

2.  Scope

   The purpose of this memo is to foster repeatable measurement results
   in modern networks by highlighting the key aspects of test streams
   and packets and make them part of the IPPM performance metric

   The scope is to update key sections of [RFC2330], adding
   considerations that will aid the development of new measurement
   methodologies intended for today's IP networks.  Specifically, this
   memo describes useful stream parameters in addition to the
   information in Section 11.1 of [RFC2330] and described in [RFC3432]
   for periodic streams.

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   The memo also provides new considerations to update the criteria for
   metrics in section 4 of [RFC2330], the measurement methodology in
   section 6.2 of [RFC2330], and other topics related to the quality of
   metrics and methods (see section 4).

   Other topics in [RFC2330] which might be updated or augmented are
   deferred to future work.  This includes the topics of passive and
   various forms of of hybrid active/passive measurements.

3.  New or Revised Stream Parameters

   There are several areas where measurement methodology definition and
   test result interpretation will benefit from an increased
   understanding of the stream characteristics and the (possibly
   unknown) network condition that influence the measured metrics.

   1.  Network treatment depends on the fullest extent on the "packet of
       Type-P" definition in [RFC2330], and has for some time.

       *  State is often maintained on the per-flow basis at various
          points in the path, where "flows" are determined by IP and
          other layers.  Significant treatment differences occur with
          the simplest of Type-P parameters: packet length.  Use of
          multiple lengths is RECOMMENDED.

       *  Payload content optimization (compression or format
          conversion) in intermediate segments.  This breaks the
          convention of payload correspondence when correlating
          measurements made at different points in a path.

   2.  Packet history (instantaneous or recent test rate or inactivity,
       also for non-test traffic) profoundly influences measured
       performance, in addition to all the Type-P parameters described
       in [RFC2330].

   3.  Access technology may change during testing.  A range of transfer
       capacities and access methods may be encountered during a test
       session.  When different interfaces are used, the host seeking
       access will be aware of the technology change which
       differentiates this form of path change from other changes in
       network state.  Section 14 of [RFC2330] treats the possibility
       that a host may have more than one attachment to the network, and
       also that assessment of the measurement path (route) is valid for
       some length of time (in Section 5 and Section 7 of [RFC2330]).
       Here we combine these two considerations under the assumption
       that changes may be more frequent and possibly have greater
       consequences on performance metrics.

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   4.  Paths including links or nodes with time-slotted service
       opportunities represent several challenges to measurement (when
       service time period is appreciable):

       *  Random/unbiased sampling is not possible beyond one such link
          in the path.

       *  The above encourages a segmented approach to end to end
          measurement, as described in [RFC6049] for Network
          Characterization (as defined in [RFC6703]) to understand the
          full range of delay and delay variation on the path.
          Alternatively, if application performance estimation is the
          goal (also defined in [RFC6703]), then a stream with un-biased
          or known-bias properties [RFC3432] may be sufficient.

       *  Multi-modal delay variation makes central statistics
          unimportant, others must be used instead.

   Each of these topics is treated in detail below.

3.1.  Test Packet Type-P

   We recommend two Type-P parameters to be added to the factors which
   have impact on path performance measurements, namely packet length
   and payload type.  Carefully choosing these parameters can improve
   measurement methodologies in their continuity and repeatability when
   deployed in reactive paths.

3.1.1.  Multiple Test Packet Lengths

   Many instances of network characterization using IPPM metrics have
   relied on a single test packet length.  When testing to assess
   application performance or an aggregate of traffic, benchmarking
   methods have used a range of fixed lengths and frequently augmented
   fixed size tests with a mixture of sizes, or IMIX as described in

   Test packet length influences delay measurements, in that the IPPM
   one-way delay metric [RFC2679] includes serialization time in its
   first-bit to last bit time stamping requirements.  However, different
   sizes can have a larger influence on link delay and link delay
   variation than serialization would explain alone.  This effect can be
   non-linear and change the instantaneous network performance when a
   different size is used, or the performance of packets following the
   size change.

   Repeatability is a main measurement methodology goal as stated in
   section 6.2 of [RFC2330].  To eliminate packet length as a potential

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   measurement uncertainty factor, successive measurements must use
   identical traffic patterns.  In practice a combination of random
   payload and random start time can yield representative results as
   illustrated in [IRR].

3.1.2.  Test Packet Payload Content Optimization

   The aim for efficient network resource use has resulted in deployment
   of server-only or client-server lossless or lossy payload compression
   techniques on some links or paths.  These optimizers attempt to
   compress high-volume traffic in order to reduce network load.  Files
   are analyzed by application-layer parsers, and parts (like comments)
   might be dropped.  Although typically acting on HTTP or JPEG files,
   compression might affect measurement packets, too.  In particular,
   measurement packets are qualified for efficient compression when they
   use standard plain-text payload.

   IPPM-conforming measurements should add packet payload content as a
   Type-P parameter which can help to improve measurement determinism.
   Some packet payloads are more susceptible to compression than others,
   but optimizers in the measurement path can be out ruled by using
   incompressible packet payload.  This payload content could be either
   generated by a random device or by using part of a compressed file
   (e.g., a part of a ZIP compressed archive).

   Optimization can go beyond the scope of one single data- or
   measurement stream.  Many more client- or network-centric
   optimization technologies have been proposed or standardized so far,
   including Robust Header Compression (ROHC) and Voice over IP
   aggregation as presented for instance in [EEAW].  The trend towards
   optimization being ubiquitous, many more of these technologies will
   follow.  As general observation, the more concurrent flows an
   intermediate host treats and the longer the paths shared by flows
   are, the higher becomes the incentive of hosts to aggregate flows
   belonging to distinct sources.  Measurements should consider this
   potential additional source of uncertainty with respect to
   repeatability.  Aggregation of flows in networking devices can, for
   instance, result in reciprocal timing and performance influence of
   these flows which may exceed typical reciprocical queueing effects by
   orders of magnitude.

3.2.  Packet History

   Recent packet history and instantaneous data rate influence
   measurement results for reactive links supporting on-demand capacity
   allocation.  Measurement uncertainty may be reduced by knowledge of
   measurement packet history and total host load.  Additionally, small

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   changes in history, e.g., because of lost packets along the path, can
   be the cause of large performance variations.

   For instance, delay in reactive 3G networks like High Speed Packet
   Access (HSPA) depends to a large extent on the test traffic data
   rate.  The reactive resource allocation strategy in these networks
   affects the uplink direction in particular.  Small changes in data
   rate can be the reason of more than 200% increase in delay, depending
   on the specific packet size.  A detailed theoretical and practical
   analysis of RRC link transitions, which can cause such behavior in
   Universal Mobile Terrestrial System (UMTS) networks, is presented,
   e.g., in [RRC].

3.3.  Access Technology Change

   [RFC2330] discussed the scenario of multi-homed hosts.  If hosts
   become aware of access technology changes (e.g., because of IP
   address changes or lower layer information) and make this information
   available, measurement methodologies can use this information to
   improve measurement representativeness and relevance.

   However, today's various access network technologies can present the
   same physical interface to the host.  A host may or may not become
   aware when its access technology changes on such an interface.
   Measurements for paths which support on-demand capacity allocation
   are therefore challenging, in that it is difficult to differentiate
   between access technology changes (e.g., because of mobility) and
   reactive path behavior (e.g., because of data rate change).

3.4.  Time-Slotted Randomness Cancellation

   Time-Slotted operation of path entities - interfaces, routers or
   links - in a network path is a particular challenge for measurements,
   especially if the time slot period is substantial.  The central
   observation as an extension to Poisson stream sampling in [RFC2330]
   is that the first such time-slotted component cancels unbiased
   measurement stream sampling.  In the worst case, time-slotted
   operation converts an unbiased, random measurement packet stream into
   a periodic packet stream.  Being heavily biased, these packets may
   interact with periodic behavior of subsequent time-slotted network

   Time-slotted randomness cancellation (TSRC) sources can be found in
   virtually any system, network component or path, their impact on
   measurements being a matter of the order of magnitude when compared
   to the metric under observation.  Examples of TSRC sources include
   but are not limited to system clock resolution, operating system
   ticks, time-slotted component or network operation, etc.  The amount

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   of measurement bias is determined by the particular measurement
   stream, relative offset between allocated time-slots in subsequent
   path entities, delay variation in these paths, and other sources of
   variation.  Measurement results might change over time, depending on
   how accurately the sending host, receiving host, and time-slotted
   components in the measurement path are synchronized to each other and
   to global time.  If path segments maintain flow state, flow parameter
   change or flow re-allocations can cause substantial variation in
   measurement results.

   Practical measurements confirm that such interference limits delay
   measurement variation to a sub-set of theoretical value range.
   Measurement samples for such cases can aggregate on artificial
   limits, generating multi-modal distributions as demonstrated in
   [IRR].  In this context, the desirable measurement sample statistics
   differentiate between multi-modal delay distributions caused by
   reactive path behavior and the ones due to time-slotted interference.

   Measurement methodology selection for time-slotted paths depends to a
   large extent on the respective viewpoint.  End-to-end metrics can
   provide accurate measurement results for short-term sessions and low
   likelihood of flow state modifications.  Applications or services
   which aim at approximating path performance for a short time interval
   (in the order of minutes) and expect stable path conditions should
   therefore prefer end-to-end metrics.  Here stable path conditions
   refer to any kind of global knowledge concerning measurement path
   flow state and flow parameters.

   However, if long-term forecast of time-slotted path performance is
   the main measurement goal, a segmented approach relying on
   measurement of sub-path metrics is preferred.  Re-generating unbiased
   measurement traffic at any hop can help to reveal the true range of
   path performance for all path segments.

4.  Quality of Metrics and Methodologies

   [RFC6808] proposes repeatability and continuity as one of the metric
   and methodology properties to infer on measurement quality.
   Depending mainly on the set of controlled measurement parameters,
   measurements repeated for a specific network path using a specific
   methodology may or may not yield repeatable results.  Challenging
   measurement scenarios for adequate parameter control include
   wireless, reactive, or time-slotted networks as discussed earlier in
   this document.  This section presents an expanded definition of
   "repeatability" beyond the definition in [RFC2330] and an expanded
   examination of the [RFC2330] concept of "continuity" and its limited

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4.1.  Repeatability

   [RFC2330] defines repeatability in a general way:

   "A methodology for a metric should have the property that it is
   repeatable: if the methodology is used multiple times under identical
   conditions, the same measurements should result in the same

   The challenge is to develop this definition further, such that it
   becomes an objective measurable criterion (and does not depend on the
   concept of continuity discussed below).  Fortunately, this topic has
   been treated in other IPPM work.  In BCP 176 [RFC6576], the criteria
   of equivalent results was agreed as the surrogate for
   interoperability when assessing metric RFCs for standards track
   advancement.  The criteria of equivalence were expressed as objective
   statistical requirements for comparison across same implementations
   and independent implementations in the test plans specific to each
   RFC evaluated ([RFC2679] in the test plan of [RFC6808]).

   The tests of [RFC6808] rely on nearly identical conditions to be
   present for analysis, but accept that these conditions cannot be
   exactly identical in the production network paths used.  The test
   plans allow some correction factors to be applied (some statistical
   tests are hyper-sensitive to differences in the mean of
   distributions), and recognize the original findings of [RFC2330]
   regarding excess sample sizes.

   One way to view the reliance on identical conditions is to view it as
   a challenge: how few parameters and path conditions need to be
   controlled and still produce repeatable methods/measurements?

   Although the [RFC6808] test plan documented numerical criteria for
   equivalence, we cannot specify the exact numerical criteria for
   repeatability *in general*. The process in the BCP [RFC6576] and
   statistics in [RFC6808] have been used successfully, and the
   numerical criteria to declare a metric repeatable should be agreed by
   all interested parties prior to measurement.

   We revise the definition slightly, as follows:

   "A methodology for a metric should have the property that it is
   repeatable: if the methodology is used multiple times under identical
   conditions, the methods should produce equivalent measurement

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4.2.  Continuity

   In the original framework [RFC2330], the concept of continuity was
   introduced to provide a relaxed criteria for judging repeatability,
   and was described in section 6.2 of [RFC2330] as follows:

   "...a methodology for a given metric exhibits continuity if, for
   small variations in conditions, it results in small variations in the
   resulting measurements."

   Although there are conditions where metrics may exhibit continuity,
   there are others where this criteria would fail for both user traffic
   and active measurement traffic.  Consider link fragmentation, and the
   non-linear increase in delay when we increase packet size just beyond
   the limit of a single fragment.  An active measurement packet would
   see the same delay increase when exceeding the fragment size.

   The Bulk Transfer Capacity (BTC) [RFC3148] gives another example at
   bottom of page 2:

   "There is also evidence that most TCP implementations exhibit non-
   linear performance over some portion of their operating region.  It
   is possible to construct simple simulation examples where incremental
   improvements to a path (such as raising the link data rate) results
   in lower overall TCP throughput (or BTC) [Mat98]."

   Clearly, the time-slotted network elements described in section 3.4
   above also qualifies as a new exception to the ideal of continuity.
   Therefore, we deprecate continuity as an alternate criterion on
   metrics, and prefer the more exact evaluation of repeatability

4.3.  Actionable

   The IP Performance Metrics Framework [RFC2330] includes usefulness as
   a metric criterion:

   "...The metrics must be useful to users and providers in
   understanding the performance they experience or provide...".

   When considering measurements as part of a maintenance process,
   evaluation of measurement results for a path under observation can
   draw attention to potential performance problems "somewhere" on the
   path.  Anomaly detection is therefore an important phase and first
   step which already satisfies the usefulness criterion for many

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   This concept of usefulness can be extended, becoming a sub-set of
   what we refer to as "actionable" criterion in the following.  Central
   to maintenance is the isolation of the root cause of reported
   anomalies down to a specific sub-path, link or host, and metrics
   should support this second step as well.  While detection of path
   anomaly may be the result of an on-going monitoring process, the
   second step of cause isolation consists of specific, directed on-
   demand measurements on components and sub-paths.  Metrics must
   support users in this directed search, becoming actionable:

   Metrics must enable users and operators to understand path
   performance and SHOULD help to direct corrective actions when
   warranted, based on the measurement results.

   Besides characterizing metrics, usefulness and actionable properties
   are also applicable to methodologies and measurements.

4.4.  Conservative

   [RFC2330] adopts the term "conservative" for measurement
   methodologies for which:

   "... the act of measurement does not modify, or only slightly
   modifies, the value of the performance metric the methodology
   attempts to measure."

   It should be noted that this definition of "conservative" in the
   sense of [RFC2330] depends to a large extent on the measurement
   path's technology and characteristics.  In particular, when deployed
   on reactive paths, sub-paths, links or hosts conforming to the
   definition in Section 1.1 of this document, measurement packets can
   originate capacity (re)allocations.  In addition, small measurement
   flow variations can result in other users on the same path perceiving
   significant variations in measurement results.

4.5.  Spatial and Temporal Composition

   Concepts related to temporal and spatial composition of metrics in
   Section 9 of [RFC2330] have been extended in [RFC5835].  [RFC5835]
   defines multiple new types of metrics, including Spatial Composition,
   Temporal Aggregation, and Spatial Aggregation.  So far, only the
   metrics for Spatial Composition have been standardized [RFC6049],
   providing the ability to estimate the performance of a complete path
   from subpath metrics.  Spatial Composition aligns with the finding of
   [TSRC], that unbiased sampling is not possible beyond the first time-
   slotted link within a measurement path.  In cases where measurement
   of subpaths is not feasible, restoring randomness of measurement
   samples when necessary is recommended as presented in [TSRC].

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4.6.  Poisson Sampling

   Section 11.1.1 of [RFC2330] describes Poisson sampling, where the
   inter-packet send times have a Poisson distribution.  A path element
   with reactive behavior sensitive to flow inactivity could change
   state if the random inter-packet time is too long.  It is recommended
   to truncate the tail of Poisson distribution to avoid reactive
   element state changes.  Truncation has been used without issue to
   ensure that minimum sample sizes can be attained in a fixed test

5.  Conclusions

   Safeguarding repeatability as a key property of measurement
   methodologies is highly challenging and sometimes impossible in
   reactive paths.  Measurements in paths with demand-driven allocation
   strategies must use a prototypical application packet stream to infer
   a specific application's performance.  Measurement repetition with
   unbiased network and flow states (e.g., by rebooting measurement
   hosts) can help to avoid interference with periodic network behavior,
   randomness being a mandatory feature for avoiding correlation with
   network timing.  Inferring the path performance between one
   measurement session or packet stream and other streams with alternate
   characteristics is generally discouraged with reactive paths because
   of the huge set of global parameters which have influence on
   instantaneous path performance.

6.  Security Considerations

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

7.  IANA Considerations

   This memo makes no requests of IANA.

8.  Acknowledgements

   The authors thank Rudiger Geib, Matt Mathis and Konstantinos
   Pentikousis for their helpful comments on this memo, and Ann Cerveny
   for her editorial review and comments that helped to improve
   readability overall.

9.  References

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9.1.  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

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

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

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

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

   [RFC5835]  Morton, A. and S. Van den Berghe, "Framework for Metric
              Composition", RFC 5835, April 2010.

   [RFC6049]  Morton, A. and E. Stephan, "Spatial Composition of
              Metrics", RFC 6049, January 2011.

   [RFC6576]  Geib, R., Morton, A., Fardid, R., and A. Steinmitz, "IP
              Performance Metrics (IPPM) Standard Advancement Testing",
              BCP 176, RFC 6576, March 2012.

   [RFC6703]  Morton, A., Ramachandran, G., and G. Maguluri, "Reporting
              IP Network Performance Metrics: Different Points of View",
              RFC 6703, August 2012.

9.2.  Informative References

   [EEAW]     Pentikousis, K., Piri, E., Pinola, J., Fitzek, F.,
              Nissilae, T., and I. Harjula, "Empirical Evaluation of
              VoIP Aggregation over a Fixed WiMAX Testbed", Proceedings
              of the 4th International Conference on Testbeds and
              research infrastructures for the development of networks
              and communities (TridentCom '08)
    , March 2008.

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   [IBD]      Fabini, J., Karner, W., Wallentin, L., and T. Baumgartner,
              "The Illusion of Being Deterministic - Application-Level
              Considerations on Delay in 3G HSPA Networks", Lecture
              Notes in Computer Science, Springer, Volume 5550, 2009, pp
              301-312 , May 2009.

   [IRR]      Fabini, J., Wallentin, L., and P. Reichl, "The Importance
              of Being Really Random: Methodological Aspects of IP-Layer
              2G and 3G Network Delay Assessment", ICC'09 Proceedings of
              the 2009 IEEE International Conference on Communications,
              doi: 10.1109/ICC.2009.5199514, June 2009.

   [Mat98]    Mathis, M., "Empirical Bulk Transfer Capacity", IP
              Performance Metrics Working Group report in Proceeding of
              the Forty Third Internet Engineering Task Force, Orlando,
              ippm-mathis-98dec.pdf, December 1998.

   [RFC3148]  Mathis, M. and M. Allman, "A Framework for Defining
              Empirical Bulk Transfer Capacity Metrics", RFC 3148, July

   [RFC6808]  Ciavattone, L., Geib, R., Morton, A., and M. Wieser, "Test
              Plan and Results Supporting Advancement of RFC 2679 on the
              Standards Track", RFC 6808, December 2012.

   [RFC6985]  Morton, A., "IMIX Genome: Specification of Variable Packet
              Sizes for Additional Testing", RFC 6985, July 2013.

   [RRC]      Peraelae, P., Barbuzzi, A., Boggia, G., and K.
              Pentikousis, "Theory and Practice of RRC State Transitions
              in UMTS Networks", IEEE Globecom 2009 Workshops doi:
              10.1109/GLOCOMW.2009.5360763, November 2009.

   [TSRC]     Fabini, J. and M. Abmayer, "Delay Measurement Methodology
              Revisited: Time-slotted Randomness Cancellation", IEEE
              Transactions on Instrumentation and Measurement
              doi:10.1109/TIM.2013.2263914, October 2013.

Authors' Addresses

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   Joachim Fabini
   Vienna University of Technology
   Gusshausstrasse 25/E389
   Vienna  1040

   Phone: +43 1 58801 38813
   Fax:   +43 1 58801 38898

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

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

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