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RFC 7312

Informational
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Advanced Stream and Sampling Framework for IP Performance Metrics (IPPM)

Updates:    2330


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Internet Engineering Task Force (IETF)                         J. Fabini
Request for Comments: 7312               Vienna University of Technology
Updates: 2330                                                  A. Morton
Category: Informational                                        AT&T Labs
ISSN: 2070-1721                                              August 2014


                 Advanced Stream and Sampling Framework
                   for IP Performance Metrics (IPPM)

Abstract

   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.

Status of This Memo

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

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

   Information about the current status of this document, any errata,
   and how to provide feedback on it may be obtained at
   http://www.rfc-editor.org/info/rfc7312.

Page 2 
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
   (http://trustee.ietf.org/license-info) 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  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Definition: Reactive Path Behavior  . . . . . . . . . . .   4
     1.2.  Requirements Language . . . . . . . . . . . . . . . . . .   5
   2.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . .   5
   3.  New or Revised Stream Parameters  . . . . . . . . . . . . . .   5
     3.1.  Test Packet Type-P  . . . . . . . . . . . . . . . . . . .   6
       3.1.1.  Multiple Test Packet Lengths  . . . . . . . . . . . .   7
       3.1.2.  Test Packet Payload Content Optimization  . . . . . .   7
     3.2.  Packet History  . . . . . . . . . . . . . . . . . . . . .   8
     3.3.  Access Technology Change  . . . . . . . . . . . . . . . .   8
     3.4.  Time-Slotted Randomness Cancellation  . . . . . . . . . .   9
   4.  Quality of Metrics and Methodologies  . . . . . . . . . . . .  10
     4.1.  Revised Definition of Repeatability . . . . . . . . . . .  10
     4.2.  Continuity No Longer an Alternative Repeatability
           Criterion . . . . . . . . . . . . . . . . . . . . . . . .  11
     4.3.  Metrics Should Be Actionable  . . . . . . . . . . . . . .  12
     4.4.  It May Not Be Possible To Be Conservative . . . . . . . .  13
     4.5.  Spatial and Temporal Composition Support Unbiased
           Sampling  . . . . . . . . . . . . . . . . . . . . . . . .  13
     4.6.  When to Truncate the Poisson Sampling Distribution  . . .  13
   5.  Conclusions . . . . . . . . . . . . . . . . . . . . . . . . .  14
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .  14
   7.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  14
   8.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  15
     8.1.  Normative References  . . . . . . . . . . . . . . . . . .  15
     8.2.  Informative References  . . . . . . . . . . . . . . . . .  16

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1.  Introduction

   The IETF IPPM working group first created a framework for metric
   development in [RFC2330].  This framework has 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 "serialization delay = packet size /
   capacity" equation, and they are state-less or history-less (with
   some exceptions, e.g., 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.  There are proposed extensions to allow methodologies to
   fulfill the continuity requirement stated in Section 6.2 of
   [RFC2330], but it is impossible to guarantee they can do so.
   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 IPPM framework [RFC2330] with advanced
   considerations for measurement methodology and testing.  We note that
   the scope of IPPM work at the time of the publication of [RFC2330]
   (and during more than a decade that followed) was limited to active
   techniques or those that generate packet streams that are dedicated
   to measurement and do not monitor user traffic.  This memo retains
   that same scope.

   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
   Type-P".

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   Among the evolutionary networking changes is a phenomenon we call
   "reactive behavior", as 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,
   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 different patterns at the
   input of the reactive host/link due to impairments in the
   intermediate subpath.  The reactive host/link is expected to provide
   a deterministic response on identical input patterns (composed of all
   flows, including the flow of interest).

   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/Inactive 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.

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1.2.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

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 making them part of the IPPM framework.

   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 that complement the
   parameters discussed in Section 11.1 of [RFC2330] and the parameters
   described in Section 4.2 of [RFC3432] for periodic streams.

   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] that might be updated or augmented are
   deferred to future work.  This includes the topics of passive and
   various forms 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 conditions 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 breaks the convention of
          payload correspondence when correlating measurements are made
          at different points in a path.

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   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] addresses 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 Sections 5 and 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.

   4.  Paths including links or nodes with time-slotted service
       opportunities represent several challenges to measurement (when
       the 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 unbiased
          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 that
   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.

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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 Internet Mix (IMIX) as
   described in [RFC6985].

   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 timestamping 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
   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.  We note that use of transport-layer
   encryption will counteract the deployment of network-based analysis
   and may reduce the adoption of payload optimizations, however.

   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
   supplied by a pseudo-random sequence generator or by using part of a
   compressed file (e.g., a part of a ZIP compressed archive).

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   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].  Where
   optimization is feasible and valuable, many more of these
   technologies may follow.  As a 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 reciprocal 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
   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 a 200% increase in delay,
   depending on the specific packet size.  A detailed theoretical and
   practical analysis of Radio Resource Control (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 that support on-demand capacity allocation
   are, therefore, challenging in that it is difficult to differentiate

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   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 entities [TSRC].

   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
   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 reallocations can cause substantial variation in
   measurement results.

   Practical measurements confirm that such interference limits delay
   measurement variation to a subset 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
   that aim at approximating path performance for a short time interval
   (in the order of minutes) and expect stable path conditions should,

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   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 subpath metrics is preferred.  Regenerating 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 concept of "continuity" in [RFC2330] and its
   limited applicability.

4.1.  Revised Definition of 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
   measurements."

   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 the 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 and accept that these conditions cannot be
   exactly identical in the production network paths used.  The test

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   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 test plan in [RFC6808] 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 results.

4.2.  Continuity No Longer an Alternative Repeatability Criterion

   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 in
   Section 1, 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].

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   Clearly, the time-slotted network elements described in Section 3.4
   of this document also qualify 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
      instead.

4.3.  Metrics Should Be 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 that already satisfies the usefulness criterion for many
   metrics.

   This concept of usefulness can be extended, becoming a subset of what
   we refer to as "actionable" criterion in the following.  We note that
   this is not the term from law.

   Central to maintenance is the isolation of the root cause of reported
   anomalies down to a specific subpath, 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 subpaths.  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.

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4.4.  It May Not Be Possible To Be 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, subpaths, 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.  Therefore:

      It is not always possible for the method to be conservative.

4.5.  Spatial and Temporal Composition Support Unbiased Sampling

   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 unbiased measurement for all segments of a path is
      not feasible due to the presence of a time-slotted link, restoring
      randomness of measurement samples when necessary is recommended as
      presented in [TSRC], in combination with Spatial Composition
      [RFC6049].

4.6.  When to Truncate the Poisson Sampling Distribution

   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
      when needed to avoid reactive element state changes.

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   Tail truncation has been used without issue to ensure that minimum
   sample sizes can be attained in a fixed-test interval.

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,
   with randomness being a mandatory feature for avoiding correlation
   with network timing.

   Inferring the path performance between one measurement session or
   packet stream and other sessions/streams with alternate
   characteristics is generally discouraged with reactive paths because
   of the huge set of global parameters that 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].

   When considering privacy of those involved in measurement or those
   whose traffic is measured, the sensitive information available to
   potential observers is greatly reduced when using active techniques
   that are within this scope of work.  Passive observations of user
   traffic for measurement purposes raise many privacy issues.  We refer
   the reader to the privacy considerations described in the Large Scale
   Measurement of Broadband Performance (LMAP) Framework [LMAP], which
   covers active and passive techniques.

7.  Acknowledgements

   The authors thank Rudiger Geib, Matt Mathis, Konstantinos
   Pentikousis, and Robert Sparks for their helpful comments on this
   memo, Alissa Cooper and Kathleen Moriarty for suggesting ways to
   "update the update" for heightened privacy awareness and its
   consequences, and Ann Cerveny for her editorial review and comments
   that helped to improve readability overall.

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8.  References

8.1.  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.

   [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.

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8.2.  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), Article No. 19, March
              2008, <http://dl.acm.org/citation.cfm?id=139059>.

   [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, Volume 5550, 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.

   [LMAP]     Eardley, P., Morton, A., Bagnulo, M., Burbridge, T.,
              Aitken, P., and A. Akhter, "A framework for large-scale
              measurement platforms (LMAP)", Work in Progress, June
              2014.

   [Mat98]    Mathis, M., "Empirical Bulk Transfer Capacity", IP
              Performance Metrics Working Group report in Proceedings of
              the Forty-Third Internet Engineering Task Force, Orlando,
              FL, December 1998,
              <http://www.ietf.org/proceedings/43/slides/
              ippm-mathis-98dec.pdf>.

   [RFC3148]  Mathis, M. and M. Allman, "A Framework for Defining
              Empirical Bulk Transfer Capacity Metrics", RFC 3148, July
              2001.

   [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.

Top      ToC       Page 17 
   [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, Volume
              62, Issue 10, doi:10.1109/TIM.2013.2263914, October 2013.

Authors' Addresses

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

   Phone: +43 1 58801 38813
   Fax:   +43 1 58801 38898
   EMail: Joachim.Fabini@tuwien.ac.at
   URI:   http://www.tc.tuwien.ac.at/about-us/staff/joachim-fabini/


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

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