draft-ietf-ippm-spatial-composition-16.txt   rfc6049.txt 
Network Working Group A. Morton Internet Engineering Task Force (IETF) A. Morton
Internet-Draft AT&T Labs Request for Comments: 6049 AT&T Labs
Intended status: Standards Track E. Stephan Category: Standards Track E. Stephan
Expires: February 14, 2011 France Telecom Division R&D ISSN: 2070-1721 France Telecom Orange
August 13, 2010 January 2011
Spatial Composition of Metrics Spatial Composition of Metrics
draft-ietf-ippm-spatial-composition-16
Abstract Abstract
This memo utilizes IP Performance Metrics that are applicable to both This memo utilizes IP performance metrics that are applicable to both
complete paths and sub-paths, and defines relationships to compose a complete paths and sub-paths, and it defines relationships to compose
complete path metric from the sub-path metrics with some accuracy a complete path metric from the sub-path metrics with some accuracy
w.r.t. the actual metrics. This is called Spatial Composition in RFC with regard to the actual metrics. This is called "spatial
2330. The memo refers to the Framework for Metric Composition, and composition" in RFC 2330. The memo refers to the framework for
provides background and motivation for combining metrics to derive metric composition, and provides background and motivation for
others. The descriptions of several composed metrics and statistics combining metrics to derive others. The descriptions of several
follow. composed metrics and statistics follow.
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].
In this memo, the characters "<=" should be read as "less than or
equal to" and ">=" as "greater than or equal to".
Status of this Memo
This Internet-Draft is submitted in full conformance with the Status of This Memo
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering This is an Internet Standards Track document.
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months This document is a product of the Internet Engineering Task Force
and may be updated, replaced, or obsoleted by other documents at any (IETF). It represents the consensus of the IETF community. It has
time. It is inappropriate to use Internet-Drafts as reference received public review and has been approved for publication by the
material or to cite them other than as "work in progress." Internet Engineering Steering Group (IESG). Further information on
Internet Standards is available in Section 2 of RFC 5741.
This Internet-Draft will expire on February 14, 2011. 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/rfc6049.
Copyright Notice Copyright Notice
Copyright (c) 2010 IETF Trust and the persons identified as the
Copyright (c) 2011 IETF Trust and the persons identified as the
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Table of Contents Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 5 1. Introduction ....................................................4
1.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . 6 1.1. Motivation .................................................6
2. Scope and Application . . . . . . . . . . . . . . . . . . . . 6 1.2. Requirements Language ......................................6
2.1. Scope of work . . . . . . . . . . . . . . . . . . . . . . 6 2. Scope and Application ...........................................6
2.2. Application . . . . . . . . . . . . . . . . . . . . . . . 7 2.1. Scope of Work ..............................................6
2.3. Incomplete Information . . . . . . . . . . . . . . . . . . 7 2.2. Application ................................................7
3. Common Specifications for Composed Metrics . . . . . . . . . . 7 2.3. Incomplete Information .....................................7
3.1. Name: Type-P . . . . . . . . . . . . . . . . . . . . . . . 8 3. Common Specifications for Composed Metrics ......................8
3.1.1. Metric Parameters . . . . . . . . . . . . . . . . . . 8 3.1. Name: Type-P ...............................................8
3.1.2. Definition and Metric Units . . . . . . . . . . . . . 9 3.1.1. Metric Parameters ...................................8
3.1.3. Discussion and other details . . . . . . . . . . . . . 9 3.1.2. Definition and Metric Units .........................9
3.1.4. Statistic: . . . . . . . . . . . . . . . . . . . . . . 9 3.1.3. Discussion and Other Details ........................9
3.1.5. Composition Function . . . . . . . . . . . . . . . . . 9 3.1.4. Statistic ...........................................9
3.1.6. Statement of Conjecture and Assumptions . . . . . . . 9 3.1.5. Composition Function ................................9
3.1.7. Justification of the Composition Function . . . . . . 9 3.1.6. Statement of Conjecture and Assumptions ............10
3.1.8. Sources of Deviation from the Ground Truth . . . . . . 10 3.1.7. Justification of the Composition Function ..........10
3.1.9. Specific cases where the conjecture might fail . . . . 11 3.1.8. Sources of Deviation from the Ground Truth .........10
3.1.10. Application of Measurement Methodology . . . . . . . . 11 3.1.9. Specific Cases where the Conjecture Might Fail .....11
4. One-way Delay Composed Metrics and Statistics . . . . . . . . 12 3.1.10. Application of Measurement Methodology ............12
4.1. Name: Type-P-Finite-One-way-Delay-<Sample>-Stream . . . . 12 4. One-Way Delay Composed Metrics and Statistics ..................12
4.1.1. Metric Parameters . . . . . . . . . . . . . . . . . . 12 4.1. Name: Type-P-Finite-One-way-Delay-<Sample>-Stream .........12
4.1.2. Definition and Metric Units . . . . . . . . . . . . . 12 4.1.1. Metric Parameters ..................................12
4.1.3. Discussion and other details . . . . . . . . . . . . . 12 4.1.2. Definition and Metric Units ........................12
4.1.4. Statistic: . . . . . . . . . . . . . . . . . . . . . . 13 4.1.3. Discussion and Other Details .......................13
4.2. Name: Type-P-Finite-Composite-One-way-Delay-Mean . . . . . 13 4.1.4. Statistic ..........................................13
4.2.1. Metric Parameters . . . . . . . . . . . . . . . . . . 13 4.2. Name: Type-P-Finite-Composite-One-way-Delay-Mean ..........13
4.2.2. Definition and Metric Units of the Mean Statistic . . 13 4.2.1. Metric Parameters ..................................13
4.2.3. Discussion and other details . . . . . . . . . . . . . 14 4.2.2. Definition and Metric Units of the Mean Statistic ..14
4.2.4. Statistic: . . . . . . . . . . . . . . . . . . . . . . 14 4.2.3. Discussion and Other Details .......................14
4.2.5. Composition Function: Sum of Means . . . . . . . . . . 14 4.2.4. Statistic ..........................................14
4.2.6. Statement of Conjecture and Assumptions . . . . . . . 14 4.2.5. Composition Function: Sum of Means .................14
4.2.7. Justification of the Composition Function . . . . . . 14 4.2.6. Statement of Conjecture and Assumptions ............15
4.2.8. Sources of Deviation from the Ground Truth . . . . . . 14 4.2.7. Justification of the Composition Function ..........15
4.2.9. Specific cases where the conjecture might fail . . . . 15 4.2.8. Sources of Deviation from the Ground Truth .........15
4.2.10. Application of Measurement Methodology . . . . . . . . 15 4.2.9. Specific Cases where the Conjecture Might Fail .....15
4.3. Name: Type-P-Finite-Composite-One-way-Delay-Minimum . . . 15 4.2.10. Application of Measurement Methodology ............16
4.3.1. Metric Parameters . . . . . . . . . . . . . . . . . . 15 4.3. Name: Type-P-Finite-Composite-One-way-Delay-Minimum .......16
4.3.2. Definition and Metric Units of the Minimum 4.3.1. Metric Parameters ..................................16
Statistic . . . . . . . . . . . . . . . . . . . . . . 15 4.3.2. Definition and Metric Units of the Minimum
4.3.3. Discussion and other details . . . . . . . . . . . . . 16 Statistic ..........................................16
4.3.4. Statistic: . . . . . . . . . . . . . . . . . . . . . . 16 4.3.3. Discussion and Other Details .......................16
4.3.5. Composition Function: Sum of Minima . . . . . . . . . 16 4.3.4. Statistic ..........................................16
4.3.6. Statement of Conjecture and Assumptions . . . . . . . 16 4.3.5. Composition Function: Sum of Minima ................16
4.3.7. Justification of the Composition Function . . . . . . 16 4.3.6. Statement of Conjecture and Assumptions ............17
4.3.8. Sources of Deviation from the Ground Truth . . . . . . 16 4.3.7. Justification of the Composition Function ..........17
4.3.9. Specific cases where the conjecture might fail . . . . 17 4.3.8. Sources of Deviation from the Ground Truth .........17
4.3.10. Application of Measurement Methodology . . . . . . . . 17 4.3.9. Specific Cases where the Conjecture Might Fail .....17
5. Loss Metrics and Statistics . . . . . . . . . . . . . . . . . 17 4.3.10. Application of Measurement Methodology ............17
5.1. Type-P-Composite-One-way-Packet-Loss-Empirical-Probability 17 5. Loss Metrics and Statistics ....................................18
5.1.1. Metric Parameters: . . . . . . . . . . . . . . . . . . 17 5.1. Type-P-Composite-One-way-Packet-Loss-Empirical-Probability 18
5.1.2. Definition and Metric Units . . . . . . . . . . . . . 17 5.1.1. Metric Parameters ..................................18
5.1.3. Discussion and other details . . . . . . . . . . . . . 17 5.1.2. Definition and Metric Units ........................18
5.1.4. Statistic: 5.1.3. Discussion and Other Details .......................18
Type-P-One-way-Packet-Loss-Empirical-Probability . . . 17 5.1.4. Statistic:
5.1.5. Composition Function: Composition of Empirical Type-P-One-way-Packet-Loss-Empirical-Probability ...18
Probabilities . . . . . . . . . . . . . . . . . . . . 18 5.1.5. Composition Function: Composition of
5.1.6. Statement of Conjecture and Assumptions . . . . . . . 18 Empirical Probabilities ............................18
5.1.7. Justification of the Composition Function . . . . . . 18 5.1.6. Statement of Conjecture and Assumptions ............19
5.1.8. Sources of Deviation from the Ground Truth . . . . . . 18 5.1.7. Justification of the Composition Function ..........19
5.1.9. Specific cases where the conjecture might fail . . . . 18 5.1.8. Sources of Deviation from the Ground Truth .........19
5.1.10. Application of Measurement Methodology . . . . . . . . 19 5.1.9. Specific Cases where the Conjecture Might Fail .....19
6. Delay Variation Metrics and Statistics . . . . . . . . . . . . 19 5.1.10. Application of Measurement Methodology ............19
6.1. Name: Type-P-One-way-pdv-refmin-<Sample>-Stream . . . . . 19 6. Delay Variation Metrics and Statistics .........................20
6.1.1. Metric Parameters: . . . . . . . . . . . . . . . . . . 19 6.1. Name: Type-P-One-way-pdv-refmin-<Sample>-Stream ...........20
6.1.2. Definition and Metric Units . . . . . . . . . . . . . 20 6.1.1. Metric Parameters ..................................20
6.1.3. Discussion and other details . . . . . . . . . . . . . 20 6.1.2. Definition and Metric Units ........................20
6.1.4. Statistics: Mean, Variance, Skewness, Quantile . . . . 20 6.1.3. Discussion and Other Details .......................21
6.1.5. Composition Functions: . . . . . . . . . . . . . . . . 21 6.1.4. Statistics: Mean, Variance, Skewness, Quantile .....21
6.1.6. Statement of Conjecture and Assumptions . . . . . . . 22 6.1.5. Composition Functions ..............................22
6.1.7. Justification of the Composition Function . . . . . . 23 6.1.6. Statement of Conjecture and Assumptions ............23
6.1.8. Sources of Deviation from the Ground Truth . . . . . . 23 6.1.7. Justification of the Composition Function ..........23
6.1.9. Specific cases where the conjecture might fail . . . . 23 6.1.8. Sources of Deviation from the Ground Truth .........23
6.1.10. Application of Measurement Methodology . . . . . . . . 23 6.1.9. Specific Cases where the Conjecture Might Fail .....24
7. Security Considerations . . . . . . . . . . . . . . . . . . . 23 6.1.10. Application of Measurement Methodology ............24
7.1. Denial of Service Attacks . . . . . . . . . . . . . . . . 23 7. Security Considerations ........................................24
7.2. User Data Confidentiality . . . . . . . . . . . . . . . . 24 7.1. Denial-of-Service Attacks .................................24
7.3. Interference with the metrics . . . . . . . . . . . . . . 24 7.2. User Data Confidentiality .................................24
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 24 7.3. Interference with the Metrics .............................24
9. Contributors and Acknowledgements . . . . . . . . . . . . . . 27 8. IANA Considerations ............................................25
10. References . . . . . . . . . . . . . . . . . . . . . . . . . . 28 9. Contributors and Acknowledgements ..............................27
10.1. Normative References . . . . . . . . . . . . . . . . . . . 28 10. References ....................................................28
10.2. Informative References . . . . . . . . . . . . . . . . . . 29 10.1. Normative References .....................................28
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 10.2. Informative References ...................................28
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 29
1. Introduction 1. Introduction
The IP Performance Metrics (IPPM) framework [RFC2330] describes two The IP Performance Metrics (IPPM) framework [RFC2330] describes two
forms of metric composition, spatial and temporal. The composition forms of metric composition: spatial and temporal. The composition
framework [RFC5835] expands and further qualifies these original framework [RFC5835] expands and further qualifies these original
forms into three categories. This memo describes Spatial forms into three categories. This memo describes spatial
Composition, one of the categories of metrics under the umbrella of composition, one of the categories of metrics under the umbrella of
the composition framework. the composition framework.
Spatial composition encompasses the definition of performance metrics Spatial composition encompasses the definition of performance metrics
that are applicable to a complete path, based on metrics collected on that are applicable to a complete path, based on metrics collected on
various sub-paths. various sub-paths.
The main purpose of this memo is to define the deterministic The main purpose of this memo is to define the deterministic
functions that yield the complete path metrics using metrics of the functions that yield the complete path metrics using metrics of the
sub-paths. The effectiveness of such metrics is dependent on their sub-paths. The effectiveness of such metrics is dependent on their
usefulness in analysis and applicability with practical measurement usefulness in analysis and applicability with practical measurement
methods. methods.
The relationships may involve conjecture, and [RFC2330] lists four The relationships may involve conjecture, and [RFC2330] lists four
points that the metric definitions should include: points that the metric definitions should include:
o the specific conjecture applied to the metric and assumptions of o the specific conjecture applied to the metric and assumptions of
the statistical model of the process being measured (if any, see the statistical model of the process being measured (if any; see
[RFC2330] section 12), [RFC2330], Section 12),
o a justification of the practical utility of the composition in o a justification of the practical utility of the composition in
terms of making accurate measurements of the metric on the path, terms of making accurate measurements of the metric on the path,
o a justification of the usefulness of the composition in terms of o a justification of the usefulness of the composition in terms of
making analysis of the path using A-frame concepts more effective, making analysis of the path using A-frame concepts more effective,
and and
o an analysis of how the conjecture could be incorrect. o an analysis of how the conjecture could be incorrect.
Also, [RFC2330] gives an example using the conjecture that the delay Also, [RFC2330] gives an example using the conjecture that the delay
of a path is very nearly the sum of the delays of the exchanges and of a path is very nearly the sum of the delays of the exchanges and
clouds of the corresponding path digest. This example is clouds of the corresponding path digest. This example is
particularly relevant to those who wish to assess the performance of particularly relevant to those who wish to assess the performance of
an Inter-domain path without direct measurement, and the performance an inter-domain path without direct measurement, and the performance
estimate of the complete path is related to the measured results for estimate of the complete path is related to the measured results for
various sub-paths instead. various sub-paths instead.
Approximate functions between the sub-path and complete path metrics Approximate functions between the sub-path and complete path metrics
are useful, with knowledge of the circumstances where the are useful, with knowledge of the circumstances where the
relationships are/are not applicable. For example, we would not relationships are/are not applicable. For example, we would not
expect that delay singletons from each sub-path would sum to produce expect that delay singletons from each sub-path would sum to produce
an accurate estimate of a delay singleton for the complete path an accurate estimate of a delay singleton for the complete path
(unless all the delays were essentially constant - very unlikely). (unless all the delays were essentially constant -- very unlikely).
However, other delay statistics (based on a reasonable sample size) However, other delay statistics (based on a reasonable sample size)
may have a sufficiently large set of circumstances where they are may have a sufficiently large set of circumstances where they are
applicable. applicable.
1.1. Motivation 1.1. Motivation
One-way metrics defined in other RFCs (such as [RFC2679] and One-way metrics defined in other RFCs (such as [RFC2679] and
[RFC2680]) all assume that the measurement can be practically carried [RFC2680]) all assume that the measurement can be practically carried
out between the source and the destination of interest. Sometimes out between the source and the destination of interest. Sometimes
there are reasons that the measurement cannot be executed from the there are reasons that the measurement cannot be executed from the
source to the destination. For instance, the measurement path may source to the destination. For instance, the measurement path may
cross several independent domains that have conflicting policies, cross several independent domains that have conflicting policies,
measurement tools and methods, and measurement time assignment. The measurement tools and methods, and measurement time assignment. The
solution then may be the composition of several sub-path solution then may be the composition of several sub-path
measurements. This means each domain performs the One-way measurements. This means each domain performs the one-way
measurement on a sub path between two nodes that are involved in the measurement on a sub-path between two nodes that are involved in the
complete path following its own policy, using its own measurement complete path, following its own policy, using its own measurement
tools and methods, and using its own measurement timing. Under the tools and methods, and using its own measurement timing. Under the
appropriate conditions, one can combine the sub-path One-way metric appropriate conditions, one can combine the sub-path one-way metric
results to estimate the complete path One-way measurement metric with results to estimate the complete path one-way measurement metric with
some degree of accuracy. some degree of accuracy.
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].
In this memo, the characters "<=" should be read as "less than or
equal to" and ">=" as "greater than or equal to".
2. Scope and Application 2. Scope and Application
2.1. Scope of work 2.1. Scope of Work
For the primary IPPM metrics of Loss [RFC2680], Delay [RFC2679], and For the primary IP Performance Metrics RFCs for loss [RFC2680], delay
Delay Variation [RFC3393], this memo gives a set of metrics that can [RFC2679], and delay variation [RFC3393], this memo gives a set of
be composed from the same or similar sub-path metrics. This means metrics that can be composed from the same or similar sub-path
that the composition function may utilize: metrics. This means that the composition function may utilize:
o the same metric for each sub-path; o the same metric for each sub-path;
o multiple metrics for each sub-path (possibly one that is the same o multiple metrics for each sub-path (possibly one that is the same
as the complete path metric); as the complete path metric);
o a single sub-path metric that is different from the complete path o a single sub-path metric that is different from the complete path
metric; metric;
o different measurement techniques like active [RFC2330], [RFC3432] o different measurement techniques like active [RFC2330], [RFC3432]
and passive [RFC5474]. and passive [RFC5474].
We note a possibility: Using a complete path metric and all but one We note a possibility: using a complete path metric and all but one
sub-path metric to infer the performance of the missing sub-path, sub-path metric to infer the performance of the missing sub-path,
especially when the "last" sub-path metric is missing. However, such especially when the "last" sub-path metric is missing. However, such
de-composition calculations, and the corresponding set of issues they de-composition calculations, and the corresponding set of issues they
raise, are beyond the scope of this memo. raise, are beyond the scope of this memo.
2.2. Application 2.2. Application
The composition framework [RFC5835] requires the specification of the The composition framework [RFC5835] requires the specification of the
applicable circumstances for each metric. In particular, each applicable circumstances for each metric. In particular, each
section addresses whether the metric: section addresses whether the metric:
Requires the same test packets to traverse all sub-paths, or may use o Requires the same test packets to traverse all sub-paths or may
similar packets sent and collected separately in each sub-path. use similar packets sent and collected separately in each
sub-path.
Requires homogeneity of measurement methodologies, or can allow a o Requires homogeneity of measurement methodologies or can allow a
degree of flexibility (e.g., active or passive methods produce the degree of flexibility (e.g., active, active spatial division
"same" metric). Also, the applicable sending streams will be [RFC5644], or passive methods produce the "same" metric). Also,
specified, such as Poisson, Periodic, or both. the applicable sending streams will be specified, such as Poisson,
Periodic, or both.
Needs information or access that will only be available within an o Needs information or access that will only be available within an
operator's domain, or is applicable to Inter-domain composition. operator's domain, or is applicable to inter-domain composition.
Requires synchronized measurement start and stop times in all sub- o Requires synchronized measurement start and stop times in all
paths, or largely overlapping, or no timing requirements. sub-paths or largely overlapping measurement intervals, or no
timing requirements.
Requires assumption of sub-path independence w.r.t. the metric being o Requires the assumption of sub-path independence with regard to
defined/composed, or other assumptions. the metric being defined/composed or other assumptions.
Has known sources of inaccuracy/error, and identifies the sources. o Has known sources of inaccuracy/error and identifies the sources.
2.3. Incomplete Information 2.3. Incomplete Information
In practice, when measurements cannot be initiated on a sub-path (and In practice, when measurements cannot be initiated on a sub-path (and
perhaps the measurement system gives up during the test interval), perhaps the measurement system gives up during the test interval),
then there will not be a value for the sub-path reported, and the then there will not be a value for the sub-path reported, and the
entire test result SHOULD be recorded as "undefined". This case entire test result SHOULD be recorded as "undefined". This case
should be distinguished from the case where the measurement system should be distinguished from the case where the measurement system
continued to send packets throughout the test interval, but all were continued to send packets throughout the test interval, but all were
declared lost. declared lost.
When a composed metric requires measurements from sub paths A, B, and When a composed metric requires measurements from sub-paths A, B, and
C, and one or more of the sub-path results are undefined, then the C, and one or more of the sub-path results are undefined, then the
composed metric SHOULD also be recorded as undefined. composed metric SHOULD also be recorded as undefined.
3. Common Specifications for Composed Metrics 3. Common Specifications for Composed Metrics
To reduce the redundant information presented in the detailed metrics To reduce the redundant information presented in the detailed metrics
sections that follow, this section presents the specifications that sections that follow, this section presents the specifications that
are common to two or more metrics. The section is organized using are common to two or more metrics. The section is organized using
the same subsections as the individual metrics, to simplify the same subsections as the individual metrics, to simplify
comparisons. comparisons.
Also, the following index variables represent the following: Also, the index variables are represented as follows:
o m = index for packets sent o m = index for packets sent.
o n = index for packets received o n = index for packets received.
o s = index for involved sub-paths o s = index for involved sub-paths.
3.1. Name: Type-P 3.1. Name: Type-P
All metrics use the Type-P convention as described in [RFC2330]. The All metrics use the "Type-P" convention as described in [RFC2330].
rest of the name is unique to each metric. The rest of the name is unique to each metric.
3.1.1. Metric Parameters 3.1.1. Metric Parameters
o Src, the IP address of a host o Src, the IP address of a host.
o Dst, the IP address of a host o Dst, the IP address of a host.
o T, a time (start of test interval) o T, a time (start of test interval).
o Tf, a time (end of test interval) o Tf, a time (end of test interval).
o lambda, a rate in reciprocal seconds (for Poisson Streams) o lambda, a rate in reciprocal seconds (for Poisson Streams).
o incT, the nominal duration of inter-packet interval, first bit to o incT, the nominal duration of inter-packet interval, first bit to
first bit (for Periodic Streams) first bit (for Periodic Streams).
o T0, a time that MUST be selected at random from the interval [T, o dT, the duration of the allowed interval for Periodic Stream
T+dT] to start generating packets and taking measurements (for sample start times.
Periodic Streams)
o T0, a time that MUST be selected at random from the interval
[T, T + dT] to start generating packets and taking measurements
(for Periodic Streams).
o TstampSrc, the wire time of the packet as measured at MP(Src) o TstampSrc, the wire time of the packet as measured at MP(Src)
(measurement point at the source).
o TstampDst, the wire time of the packet as measured at MP(Dst), o TstampDst, the wire time of the packet as measured at MP(Dst),
assigned to packets that arrive within a "reasonable" time. assigned to packets that arrive within a "reasonable" time.
o Tmax, a maximum waiting time for packets at the destination, set o Tmax, a maximum waiting time for packets at the destination, set
sufficiently long to disambiguate packets with long delays from sufficiently long to disambiguate packets with long delays from
packets that are discarded (lost), thus the distribution of delay packets that are discarded (lost); thus, the distribution of delay
is not truncated. is not truncated.
o M, the total number of packets sent between T0 and Tf o M, the total number of packets sent between T0 and Tf.
o N, the total number of packets received at Dst (sent between T0 o N, the total number of packets received at Dst (sent between T0
and Tf) and Tf).
o S, the number of sub-paths involved in the complete Src-Dst path o S, the number of sub-paths involved in the complete Src-Dst path.
o Type-P, as defined in [RFC2330], which includes any field that may o Type-P, as defined in [RFC2330], which includes any field that may
affect a packet's treatment as it traverses the network affect a packet's treatment as it traverses the network.
In metric names, the term <Sample> is intended to be replaced by the In metric names, the term "<Sample>" is intended to be replaced by
name of the method used to define a sample of values of parameter the name of the method used to define a sample of values of parameter
TstampSrc. This can be done in several ways, including: TstampSrc. This can be done in several ways, including:
1. Poisson: a pseudo-random Poisson process of rate lambda, whose 1. Poisson: a pseudo-random Poisson process of rate lambda, whose
values fall between T and Tf. The time interval between values fall between T and Tf. The time interval between
successive values of TstampSrc will then average 1/lambda, as per successive values of TstampSrc will then average 1/lambda, as per
[RFC2330]. [RFC2330].
2. Periodic: a periodic stream process with pseudo-random start time 2. Periodic: a Periodic stream process with pseudo-random start time
T0 between T and dT, and nominal inter-packet interval incT, as T0 between T and dT, and nominal inter-packet interval incT, as
per [RFC3432]. per [RFC3432].
3.1.2. Definition and Metric Units 3.1.2. Definition and Metric Units
This section is unique for every metric. This section is unique for every metric.
3.1.3. Discussion and other details 3.1.3. Discussion and Other Details
This section is unique for every metric. This section is unique for every metric.
3.1.4. Statistic: 3.1.4. Statistic
This section is unique for every metric. This section is unique for every metric.
3.1.5. Composition Function 3.1.5. Composition Function
This section is unique for every metric. This section is unique for every metric.
3.1.6. Statement of Conjecture and Assumptions 3.1.6. Statement of Conjecture and Assumptions
This section is unique for each metric. The term "ground truth" This section is unique for each metric. The term "ground truth" is
frequently used in these sections and it is defined in section 4.7 of frequently used in these sections and is defined in Section 4.7 of
[RFC5835]. [RFC5835].
3.1.7. Justification of the Composition Function 3.1.7. Justification of the Composition Function
It is sometimes impractical to conduct active measurements between It is sometimes impractical to conduct active measurements between
every Src-Dst pair. Since the full mesh of N measurement points every Src-Dst pair. Since the full mesh of N measurement points
grows as N x N, the scope of measurement may be limited by testing grows as N x N, the scope of measurement may be limited by testing
resources. resources.
There may be varying limitations on active testing in different parts There may be varying limitations on active testing in different parts
of the network. For example, it may not be possible to collect the of the network. For example, it may not be possible to collect the
desired sample size in each test interval when access link speed is desired sample size in each test interval when access link speed is
limited, because of the potential for measurement traffic to degrade limited, because of the potential for measurement traffic to degrade
the user traffic performance. The conditions on a low-speed access the user traffic performance. The conditions on a low-speed access
link may be understood well-enough to permit use of a small sample link may be understood well enough to permit use of a small sample
size/rate, while a larger sample size/rate may be used on other sub- size/rate, while a larger sample size/rate may be used on other
paths. sub-paths.
Also, since measurement operations have a real monetary cost, there Also, since measurement operations have a real monetary cost, there
is value in re-using measurements where they are applicable, rather is value in re-using measurements where they are applicable, rather
than launching new measurements for every possible source-destination than launching new measurements for every possible source-destination
pair. pair.
3.1.8. Sources of Deviation from the Ground Truth 3.1.8. Sources of Deviation from the Ground Truth
3.1.8.1. Sub-path List Differs from Complete Path 3.1.8.1. Sub-Path List Differs from Complete Path
The measurement packets, each having source and destination addresses The measurement packets, each having source and destination addresses
intended for collection at edges of the sub-path, may take a intended for collection at edges of the sub-path, may take a
different specific path through the network equipment and links when different specific path through the network equipment and links when
compared to packets with the source and destination addresses of the compared to packets with the source and destination addresses of the
complete path. Examples sources of parallel paths include Equal Cost complete path. Example sources of parallel paths include Equal Cost
Multi-Path and parallel (or bundled) links. Therefore, the Multi-Path and parallel (or bundled) links. Therefore, the
performance estimated from the composition of sub-path measurements performance estimated from the composition of sub-path measurements
may differ from the performance experienced by packets on the may differ from the performance experienced by packets on the
complete path. Multiple measurements employing sufficient sub-path complete path. Multiple measurements employing sufficient sub-path
address pairs might produce bounds on the extent of this error. address pairs might produce bounds on the extent of this error.
We also note the possibility of re-routing during a measurement We also note the possibility of re-routing during a measurement
interval, as it may affect the correspondence between packets interval, as it may affect the correspondence between packets
traversing the complete path and the sub-paths that were "involved" traversing the complete path and the sub-paths that were "involved"
prior to the re-route. prior to the re-route.
3.1.8.2. Sub-path Contains Extra Network Elements 3.1.8.2. Sub-Path Contains Extra Network Elements
Related to the case of an alternate path described above is the case Related to the case of an alternate path described above is the case
where elements in the measured path are unique to measurement system where elements in the measured path are unique to measurement system
connectivity. For example, a measurement system may use a dedicated connectivity. For example, a measurement system may use a dedicated
link to a LAN switch, and packets on the complete path do not link to a LAN switch, and packets on the complete path do not
traverse that link. The performance of such a dedicated link would traverse that link. The performance of such a dedicated link would
be measured continuously, and its contribution to the sub-path be measured continuously, and its contribution to the sub-path
metrics SHOULD be minimized as a source of error. metrics SHOULD be minimized as a source of error.
3.1.8.3. Sub-paths Have Incomplete Coverage 3.1.8.3. Sub-Paths Have Incomplete Coverage
Measurements of sub-path performance may not cover all the network Measurements of sub-path performance may not cover all the network
elements on the complete path. For example, the network exchange elements on the complete path. For example, the network exchange
points might be excluded unless a cooperative measurement is points might be excluded unless a cooperative measurement is
conducted. In this example, test packets on the previous sub-path conducted. In this example, test packets on the previous sub-path
are received just before the exchange point and test packets on the are received just before the exchange point, and test packets on the
next sub-path are injected just after the same exchange point. next sub-path are injected just after the same exchange point.
Clearly, the set of sub-path measurements SHOULD cover all critical Clearly, the set of sub-path measurements SHOULD cover all critical
network elements in the complete path. network elements in the complete path.
3.1.8.4. Absence of route 3.1.8.4. Absence of Route
At a specific point in time, no viable route exists between the At a specific point in time, no viable route exists between the
complete path source and destination. The routes selected for one or complete path source and destination. The routes selected for one or
more sub-paths therefore differs from the complete path. more sub-paths therefore differ from the complete path.
Consequently, spatial composition may produce finite estimation of a Consequently, spatial composition may produce finite estimation of a
ground truth metric (see section 4.7 of [RFC5835]) between a source ground truth metric (see Section 4.7 of [RFC5835]) between a source
and a destination, even when the route between them is undefined. and a destination, even when the route between them is undefined.
3.1.9. Specific cases where the conjecture might fail 3.1.9. Specific Cases where the Conjecture Might Fail
This section is unique for most metrics (see the metric-specific This section is unique for most metrics (see the metric-specific
sections). sections).
For delay-related metrics, One-way delay always depends on packet For delay-related metrics, one-way delay always depends on packet
size and link capacity, since it is measured in [RFC2679] from first size and link capacity, since it is measured in [RFC2679] from first
bit to last bit. If the size of an IP packet changes on route (due bit to last bit. If the size of an IP packet changes on its route
to encapsulation), this can influence delay performance. However, (due to encapsulation), this can influence delay performance.
the main error source may be the additional processing associated However, the main error source may be the additional processing
with encapsulation and encryption/decryption if not experienced or associated with encapsulation and encryption/decryption if not
accounted for in sub-path measurements. experienced or accounted for in sub-path measurements.
Fragmentation is a major issue for composition accuracy, since all Fragmentation is a major issue for composition accuracy, since all
metrics require all fragments to arrive before proceeding, and metrics require all fragments to arrive before proceeding, and
fragmented complete path performance is likely to be different from fragmented complete path performance is likely to be different from
performance with non-fragmented packets and composed metrics based on performance with non-fragmented packets and composed metrics based on
non-fragmented sub-path measurements. non-fragmented sub-path measurements.
Highly manipulated routing can cause measurement error if not Highly manipulated routing can cause measurement error if not
expected and compensated. For example, policy-based MPLS routing expected and compensated for. For example, policy-based MPLS routing
could modify the class of service for the sub-paths and complete could modify the class of service for the sub-paths and complete
path. path.
3.1.10. Application of Measurement Methodology 3.1.10. Application of Measurement Methodology
The methodology: o The methodology SHOULD use similar packets sent and collected
separately in each sub-path, where "similar" in this case means
SHOULD use similar packets sent and collected separately in each sub- that Type-P contains as many equal attributes as possible, while
path, where "similar" in this case means that the Type-P contains as recognizing that there will be differences. Note that Type-P
many equal attributes as possible, while recognizing that there will includes stream characteristics (e.g., Poisson, Periodic).
be differences. Note that Type-P includes stream characteristics
(e.g., Poisson, Periodic).
Allows a degree of flexibility regarding test stream generation o The methodology allows a degree of flexibility regarding test
(e.g., active or passive methods can produce an equivalent result, stream generation (e.g., active or passive methods can produce an
but the lack of control over the source, timing and correlation of equivalent result, but the lack of control over the source,
passive measurements is much more challenging). timing, and correlation of passive measurements is much more
challenging).
Poisson and/or Periodic streams are RECOMMENDED. o Poisson and/or Periodic streams are RECOMMENDED.
Applies to both Inter-domain and Intra-domain composition. o The methodology applies to both inter-domain and intra-domain
composition.
SHOULD have synchronized measurement time intervals in all sub-paths, o The methodology SHOULD have synchronized measurement time
but largely overlapping intervals MAY suffice. intervals in all sub-paths, but largely overlapping intervals MAY
suffice.
Assumption of sub-path independence w.r.t. the metric being defined/ o Assumption of sub-path independence with regard to the metric
composed is REQUIRED. being defined/composed is REQUIRED.
4. One-way Delay Composed Metrics and Statistics 4. One-Way Delay Composed Metrics and Statistics
4.1. Name: Type-P-Finite-One-way-Delay-<Sample>-Stream 4.1. Name: Type-P-Finite-One-way-Delay-<Sample>-Stream
This metric is a necessary element of Delay Composition metrics, and This metric is a necessary element of delay composition metrics, and
its definition does not formally exist elsewhere in IPPM literature. its definition does not formally exist elsewhere in IPPM literature.
4.1.1. Metric Parameters 4.1.1. Metric Parameters
See the common parameters section above. See the common parameters section (Section 3.1.1).
4.1.2. Definition and Metric Units 4.1.2. Definition and Metric Units
Using the parameters above, we obtain the value of Type-P-One-way- Using the parameters above, we obtain the value of the Type-P-One-
Delay singleton as per [RFC2679]. way-Delay singleton as per [RFC2679].
For each packet [i] that has a finite One-way Delay (in other words, For each packet "[i]" that has a finite one-way delay (in other
excluding packets which have undefined one-way delay): words, excluding packets that have undefined one-way delay):
Type-P-Finite-One-way-Delay-<Sample>-Stream[i] = Type-P-Finite-One-way-Delay-<Sample>-Stream[i] =
FiniteDelay[i] = TstampDst - TstampSrc FiniteDelay[i] = TstampDst - TstampSrc
The units of measure for this metric are time in seconds, expressed This metric is measured in units of time in seconds, expressed in
in sufficiently low resolution to convey meaningful quantitative sufficiently low resolution to convey meaningful quantitative
information. For example, resolution of microseconds is usually information. For example, resolution of microseconds is usually
sufficient. sufficient.
4.1.3. Discussion and other details 4.1.3. Discussion and Other Details
The "Type-P-Finite-One-way-Delay" metric permits calculation of the The "Type-P-Finite-One-way-Delay" metric permits calculation of the
sample mean statistic. This resolves the problem of including lost sample mean statistic. This resolves the problem of including lost
packets in the sample (whose delay is undefined), and the issue with packets in the sample (whose delay is undefined) and the issue with
the informal assignment of infinite delay to lost packets (practical the informal assignment of infinite delay to lost packets (practical
systems can only assign some very large value). systems can only assign some very large value).
The Finite-One-way-Delay approach handles the problem of lost packets The Finite-One-way-Delay approach handles the problem of lost packets
by reducing the event space. We consider conditional statistics, and by reducing the event space. We consider conditional statistics, and
estimate the mean one-way delay conditioned on the event that all estimate the mean one-way delay conditioned on the event that all
packets in the sample arrive at the destination (within the specified packets in the sample arrive at the destination (within the specified
waiting time, Tmax). This offers a way to make some valid statements waiting time, Tmax). This offers a way to make some valid statements
about one-way delay, and at the same time avoiding events with about one-way delay, at the same time avoiding events with undefined
undefined outcomes. This approach is derived from the treatment of outcomes. This approach is derived from the treatment of lost
lost packets in [RFC3393], and is similar to [Y.1540] . packets in [RFC3393], and is similar to [Y.1540].
4.1.4. Statistic: 4.1.4. Statistic
All statistics defined in [RFC2679] are applicable to the finite one- All statistics defined in [RFC2679] are applicable to the finite one-
way delay,and additional metrics are possible, such as the mean (see way delay, and additional metrics are possible, such as the mean (see
below). below).
4.2. Name: Type-P-Finite-Composite-One-way-Delay-Mean 4.2. Name: Type-P-Finite-Composite-One-way-Delay-Mean
This section describes a statistic based on the Type-P-Finite-One- This section describes a statistic based on the Type-P-Finite-One-
way-Delay-<Sample>-Stream metric. way-Delay-<Sample>-Stream metric.
4.2.1. Metric Parameters 4.2.1. Metric Parameters
See the common parameters section above. See the common parameters section (Section 3.1.1).
4.2.2. Definition and Metric Units of the Mean Statistic 4.2.2. Definition and Metric Units of the Mean Statistic
We define We define
Type-P-Finite-One-way-Delay-Mean = Type-P-Finite-One-way-Delay-Mean =
N N
--- ---
1 \ 1 \
= MeanDelay = - * > (FiniteDelay [n]) MeanDelay = - * > (FiniteDelay [n])
N / N /
--- ---
n = 1 n = 1
where all packets n= 1 through N have finite singleton delays. where all packets n = 1 through N have finite singleton delays.
The units of measure for this metric are time in seconds, expressed This metric is measured in units of time in seconds, expressed in
in sufficiently fine resolution to convey meaningful quantitative sufficiently fine resolution to convey meaningful quantitative
information. For example, resolution of microseconds is usually information. For example, resolution of microseconds is usually
sufficient. sufficient.
4.2.3. Discussion and other details 4.2.3. Discussion and Other Details
The Type-P-Finite-One-way-Delay-Mean metric requires the conditional The Type-P-Finite-One-way-Delay-Mean metric requires the conditional
delay distribution described in section 5.1. delay distribution described in Section 4.1.3.
4.2.4. Statistic: 4.2.4. Statistic
This metric, a mean, does not require additional statistics. This metric, a mean, does not require additional statistics.
4.2.5. Composition Function: Sum of Means 4.2.5. Composition Function: Sum of Means
The Type-P-Finite-Composite-One-way-Delay-Mean, or CompMeanDelay, for The Type-P-Finite-Composite-One-way-Delay-Mean, or CompMeanDelay, for
the complete Source to Destination path can be calculated from sum of the complete source to destination path can be calculated from the
the Mean Delays of all its S constituent sub-paths. sum of the mean delays of all of its S constituent sub-paths.
Then the Then the
Type-P-Finite-Composite-One-way-Delay-Mean = Type-P-Finite-Composite-One-way-Delay-Mean =
S S
--- ---
\ \
= CompMeanDelay = > (MeanDelay [s]) CompMeanDelay = > (MeanDelay [s])
/ /
--- ---
s = 1 s = 1
where sub-paths s = 1 to S are involved in the complete path. where sub-paths s = 1 to S are involved in the complete path.
4.2.6. Statement of Conjecture and Assumptions 4.2.6. Statement of Conjecture and Assumptions
The mean of a sufficiently large stream of packets measured on each The mean of a sufficiently large stream of packets measured on each
sub-path during the interval [T, Tf] will be representative of the sub-path during the interval [T, Tf] will be representative of the
ground truth mean of the delay distribution (and the distributions ground truth mean of the delay distribution (and the distributions
themselves are sufficiently independent), such that the means may be themselves are sufficiently independent), such that the means may be
added to produce an estimate of the complete path mean delay. added to produce an estimate of the complete path mean delay.
skipping to change at page 14, line 42 skipping to change at page 15, line 29
4.2.6. Statement of Conjecture and Assumptions 4.2.6. Statement of Conjecture and Assumptions
The mean of a sufficiently large stream of packets measured on each The mean of a sufficiently large stream of packets measured on each
sub-path during the interval [T, Tf] will be representative of the sub-path during the interval [T, Tf] will be representative of the
ground truth mean of the delay distribution (and the distributions ground truth mean of the delay distribution (and the distributions
themselves are sufficiently independent), such that the means may be themselves are sufficiently independent), such that the means may be
added to produce an estimate of the complete path mean delay. added to produce an estimate of the complete path mean delay.
It is assumed that the one-way delay distributions of the sub-paths It is assumed that the one-way delay distributions of the sub-paths
and the complete path are continuous. The mean of multi-modal and the complete path are continuous. The mean of multi-modal
distributions have the unfortunate property that such a value may distributions has the unfortunate property that such a value may
never occur. never occur.
4.2.7. Justification of the Composition Function 4.2.7. Justification of the Composition Function
See the common section. See the common section (Section 3).
4.2.8. Sources of Deviation from the Ground Truth 4.2.8. Sources of Deviation from the Ground Truth
See the common section. See the common section (Section 3).
4.2.9. Specific cases where the conjecture might fail 4.2.9. Specific Cases where the Conjecture Might Fail
If any of the sub-path distributions are multi-modal, then the If any of the sub-path distributions are multi-modal, then the
measured means may not be stable, and in this case the mean will not measured means may not be stable, and in this case the mean will not
be a particularly useful statistic when describing the delay be a particularly useful statistic when describing the delay
distribution of the complete path. distribution of the complete path.
The mean may not be a sufficiently robust statistic to produce a The mean may not be a sufficiently robust statistic to produce a
reliable estimate, or to be useful even if it can be measured. reliable estimate, or to be useful even if it can be measured.
If a link contributing non-negligible delay is erroneously included If a link contributing non-negligible delay is erroneously included
or excluded, the composition will be in error. or excluded, the composition will be in error.
4.2.10. Application of Measurement Methodology 4.2.10. Application of Measurement Methodology
The requirements of the common section apply here as well. The requirements of the common section (Section 3) apply here as
well.
4.3. Name: Type-P-Finite-Composite-One-way-Delay-Minimum 4.3. Name: Type-P-Finite-Composite-One-way-Delay-Minimum
This section describes is a statistic based on the Type-P-Finite-One- This section describes a statistic based on the Type-P-Finite-One-
way-Delay-<Sample>-Stream metric, and the composed metric based on way-Delay-<Sample>-Stream metric, and the composed metric based on
that statistic. that statistic.
4.3.1. Metric Parameters 4.3.1. Metric Parameters
See the common parameters section above. See the common parameters section (Section 3.1.1).
4.3.2. Definition and Metric Units of the Minimum Statistic 4.3.2. Definition and Metric Units of the Minimum Statistic
We define We define
Type-P-Finite-One-way-Delay-Minimum = Type-P-Finite-One-way-Delay-Minimum =
= MinDelay = (FiniteDelay [j])
such that for some index, j, where 1<= j <= N MinDelay = (FiniteDelay [j])
such that for some index, j, where 1 <= j <= N
FiniteDelay[j] <= FiniteDelay[n] for all n FiniteDelay[j] <= FiniteDelay[n] for all n
where all packets n = 1 through N have finite singleton delays. where all packets n = 1 through N have finite singleton delays.
The units of measure for this metric are time in seconds, expressed This metric is measured in units of time in seconds, expressed in
in sufficiently fine resolution to convey meaningful quantitative sufficiently fine resolution to convey meaningful quantitative
information. For example, resolution of microseconds is usually information. For example, resolution of microseconds is usually
sufficient. sufficient.
4.3.3. Discussion and other details 4.3.3. Discussion and Other Details
The Type-P-Finite-One-way-Delay-Minimum metric requires the The Type-P-Finite-One-way-Delay-Minimum metric requires the
conditional delay distribution described in section 5.1.3. conditional delay distribution described in Section 4.1.3.
4.3.4. Statistic: 4.3.4. Statistic
This metric, a minimum, does not require additional statistics. This metric, a minimum, does not require additional statistics.
4.3.5. Composition Function: Sum of Minima 4.3.5. Composition Function: Sum of Minima
The Type-P-Finite-Composite-One-way-Delay-Minimum, or CompMinDelay, The Type-P-Finite-Composite-One-way-Delay-Minimum, or CompMinDelay,
for the complete Source to Destination path can be calculated from for the complete source to destination path can be calculated from
sum of the Minimum Delays of all its S constituent sub-paths. the sum of the minimum delays of all of its S constituent sub-paths.
Then the Then the
Type-P-Finite-Composite-One-way-Delay-Minimum = Type-P-Finite-Composite-One-way-Delay-Minimum =
S S
--- ---
\ \
= CompMinDelay = > (MinDelay [s]) CompMinDelay = > (MinDelay [s])
/ /
--- ---
s = 1 s = 1
4.3.6. Statement of Conjecture and Assumptions 4.3.6. Statement of Conjecture and Assumptions
The minimum of a sufficiently large stream of packets measured on The minimum of a sufficiently large stream of packets measured on
each sub-path during the interval [T, Tf] will be representative of each sub-path during the interval [T, Tf] will be representative of
the ground truth minimum of the delay distribution (and the the ground truth minimum of the delay distribution (and the
distributions themselves are sufficiently independent), such that the distributions themselves are sufficiently independent), such that the
minima may be added to produce an estimate of the complete path minima may be added to produce an estimate of the complete path
minimum delay. minimum delay.
It is assumed that the one-way delay distributions of the sub-paths It is assumed that the one-way delay distributions of the sub-paths
and the complete path are continuous. and the complete path are continuous.
4.3.7. Justification of the Composition Function 4.3.7. Justification of the Composition Function
See the common section. See the common section (Section 3).
4.3.8. Sources of Deviation from the Ground Truth 4.3.8. Sources of Deviation from the Ground Truth
See the common section. See the common section (Section 3).
4.3.9. Specific cases where the conjecture might fail 4.3.9. Specific Cases where the Conjecture Might Fail
If the routing on any of the sub-paths is not stable, then the If the routing on any of the sub-paths is not stable, then the
measured minimum may not be stable. In this case the composite measured minimum may not be stable. In this case the composite
minimum would tend to produce an estimate for the complete path that minimum would tend to produce an estimate for the complete path that
may be too low for the current path. may be too low for the current path.
4.3.10. Application of Measurement Methodology 4.3.10. Application of Measurement Methodology
The requirements of the common section apply here as well. The requirements of the common section (Section 3) apply here as
well.
5. Loss Metrics and Statistics 5. Loss Metrics and Statistics
5.1. Type-P-Composite-One-way-Packet-Loss-Empirical-Probability 5.1. Type-P-Composite-One-way-Packet-Loss-Empirical-Probability
5.1.1. Metric Parameters: 5.1.1. Metric Parameters
Same as section 4.1.1. See the common parameters section (Section 3.1.1).
5.1.2. Definition and Metric Units 5.1.2. Definition and Metric Units
Using the parameters above, we obtain the value of Type-P-One-way- Using the parameters above, we obtain the value of the Type-P-One-
Packet-Loss singleton and stream as per [RFC2680]. way-Packet-Loss singleton and stream as per [RFC2680].
We obtain a sequence of pairs with elements as follows: We obtain a sequence of pairs with elements as follows:
o TstampSrc, as above o TstampSrc, as above.
o L, either zero or one, where L=1 indicates loss and L=0 indicates o L, either zero or one, where L = 1 indicates loss and L = 0
arrival at the destination within TstampSrc + Tmax. indicates arrival at the destination within TstampSrc + Tmax.
5.1.3. Discussion and other details 5.1.3. Discussion and Other Details
None. None.
5.1.4. Statistic: Type-P-One-way-Packet-Loss-Empirical-Probability 5.1.4. Statistic: Type-P-One-way-Packet-Loss-Empirical-Probability
Given the stream parameter M, the number of packets sent, we can Given the stream parameter M, the number of packets sent, we can
define the Empirical Probability of Loss Statistic (Ep), consistent define the Empirical Probability of Loss Statistic (Ep), consistent
with Average Loss in [RFC2680], as follows: with average loss in [RFC2680], as follows:
Type-P-One-way-Packet-Loss-Empirical-Probability = Type-P-One-way-Packet-Loss-Empirical-Probability =
M M
--- ---
1 \ 1 \
= Ep = - * > (L[m]) Ep = - * > (L[m])
M / M /
--- ---
m = 1 m = 1
where all packets m = 1 through M have a value for L. where all packets m = 1 through M have a value for L.
5.1.5. Composition Function: Composition of Empirical Probabilities 5.1.5. Composition Function: Composition of Empirical Probabilities
The Type-P-One-way-Composite-Packet-Loss-Empirical-Probability, or The Type-P-One-way-Composite-Packet-Loss-Empirical-Probability, or
CompEp for the complete Source to Destination path can be calculated CompEp, for the complete source to destination path can be calculated
by combining Ep of all its constituent sub-paths (Ep1, Ep2, Ep3, ... by combining the Ep of all of its constituent sub-paths (Ep1, Ep2,
Epn) as Ep3, ... Epn) as
Type-P-Composite-One-way-Packet-Loss-Empirical-Probability = Type-P-Composite-One-way-Packet-Loss-Empirical-Probability =
= CompEp = 1 - {(1 - Ep1) x (1 - Ep2) x (1 - Ep3) x ... x (1 - EpS)}
CompEp = 1 - {(1 - Ep1) x (1 - Ep2) x (1 - Ep3) x ... x (1 - EpS)}
If any Eps is undefined in a particular measurement interval, If any Eps is undefined in a particular measurement interval,
possibly because a measurement system failed to report a value, then possibly because a measurement system failed to report a value, then
any CompEp that uses sub-path s for that measurement interval is any CompEp that uses sub-path s for that measurement interval is
undefined. undefined.
5.1.6. Statement of Conjecture and Assumptions 5.1.6. Statement of Conjecture and Assumptions
The empirical probability of loss calculated on a sufficiently large The empirical probability of loss calculated on a sufficiently large
stream of packets measured on each sub-path during the interval [T, stream of packets measured on each sub-path during the interval
Tf] will be representative of the ground truth empirical loss [T, Tf] will be representative of the ground truth empirical loss
probability (and the probabilities themselves are sufficiently probability (and the probabilities themselves are sufficiently
independent), such that the sub-path probabilities may be combined to independent), such that the sub-path probabilities may be combined to
produce an estimate of the complete path empirical loss probability. produce an estimate of the complete path empirical loss probability.
5.1.7. Justification of the Composition Function 5.1.7. Justification of the Composition Function
See the common section. See the common section (Section 3).
5.1.8. Sources of Deviation from the Ground Truth 5.1.8. Sources of Deviation from the Ground Truth
See the common section. See the common section (Section 3).
5.1.9. Specific cases where the conjecture might fail 5.1.9. Specific Cases where the Conjecture Might Fail
A concern for loss measurements combined in this way is that root A concern for loss measurements combined in this way is that root
causes may be correlated to some degree. causes may be correlated to some degree.
For example, if the links of different networks follow the same For example, if the links of different networks follow the same
physical route, then a single catastrophic event like a fire in a physical route, then a single catastrophic event like a fire in a
tunnel could cause an outage or congestion on remaining paths in tunnel could cause an outage or congestion on remaining paths in
multiple networks. Here it is important to ensure that measurements multiple networks. Here it is important to ensure that measurements
before the event and after the event are not combined to estimate the before the event and after the event are not combined to estimate the
composite performance. composite performance.
Or, when traffic volumes rise due to the rapid spread of an email- Or, when traffic volumes rise due to the rapid spread of an email-
borne worm, loss due to queue overflow in one network may help borne worm, loss due to queue overflow in one network may help
another network to carry its traffic without loss. another network to carry its traffic without loss.
5.1.10. Application of Measurement Methodology 5.1.10. Application of Measurement Methodology
See the common section. See the common section (Section 3).
6. Delay Variation Metrics and Statistics 6. Delay Variation Metrics and Statistics
6.1. Name: Type-P-One-way-pdv-refmin-<Sample>-Stream 6.1. Name: Type-P-One-way-pdv-refmin-<Sample>-Stream
This packet delay variation (PDV) metric is a necessary element of This packet delay variation (PDV) metric is a necessary element of
Composed Delay Variation metrics, and its definition does not Composed Delay Variation metrics, and its definition does not
formally exist elsewhere in IPPM literature (with the exception of formally exist elsewhere in IPPM literature (with the exception of
[RFC5481] . [RFC5481]).
6.1.1. Metric Parameters: 6.1.1. Metric Parameters
In addition to the parameters of section 4.1.1: In addition to the parameters of Section 3.1.1:
o TstampSrc[i], the wire time of packet[i] as measured at MP(Src) o TstampSrc[i], the wire time of packet[i] as measured at MP(Src)
(measurement point at the source) (measurement point at the source).
o TstampDst[i], the wire time of packet[i] as measured at MP(Dst), o TstampDst[i], the wire time of packet[i] as measured at MP(Dst),
assigned to packets that arrive within a "reasonable" time. assigned to packets that arrive within a "reasonable" time.
o B, a packet length in bits o B, a packet length in bits.
o F, a selection function unambiguously defining the packets from o F, a selection function unambiguously defining the packets from
the stream that are selected for the packet-pair computation of the stream that are selected for the packet-pair computation of
this metric. F(current packet), the first packet of the pair, this metric. F(current packet), the first packet of the pair,
MUST have a valid Type-P-Finite-One-way-Delay less than Tmax (in MUST have a valid Type-P-Finite-One-way-Delay less than Tmax (in
other words, excluding packets which have undefined one-way delay) other words, excluding packets that have undefined one-way delay)
and MUST have been transmitted during the interval T, Tf. The and MUST have been transmitted during the interval [T, Tf]. The
second packet in the pair, F(min_delay packet) MUST be the packet second packet in the pair, F(min_delay packet) MUST be the packet
with the minimum valid value of Type-P-Finite-One-way-Delay for with the minimum valid value of Type-P-Finite-One-way-Delay for
the stream, in addition to the criteria for F(current packet). If the stream, in addition to the criteria for F(current packet). If
multiple packets have equal minimum Type-P-Finite-One-way-Delay multiple packets have equal minimum Type-P-Finite-One-way-Delay
values, then the value for the earliest arriving packet SHOULD be values, then the value for the earliest arriving packet SHOULD be
used. used.
o MinDelay, the Type-P-Finite-One-way-Delay value for F(min_delay o MinDelay, the Type-P-Finite-One-way-Delay value for F(min_delay
packet) given above. packet) given above.
o N, the number of packets received at the Destination meeting the o N, the number of packets received at the destination that meet the
F(current packet) criteria. F(current packet) criteria.
6.1.2. Definition and Metric Units 6.1.2. Definition and Metric Units
Using the definition above in section 5.1.2, we obtain the value of Using the definition above in Section 5.1.2, we obtain the value of
Type-P-Finite-One-way-Delay-<Sample>-Stream[n], the singleton for Type-P-Finite-One-way-Delay-<Sample>-Stream[n], the singleton for
each packet[i] in the stream (a.k.a. FiniteDelay[i]). each packet[i] in the stream (a.k.a. FiniteDelay[i]).
For each packet[n] that meets the F(first packet) criteria given For each packet[n] that meets the F(first packet) criteria given
above: Type-P-One-way-pdv-refmin-<Sample>-Stream[n] = above: Type-P-One-way-pdv-refmin-<Sample>-Stream[n] =
PDV[n] = FiniteDelay[n] - MinDelay PDV[n] = FiniteDelay[n] - MinDelay
where PDV[i] is in units of time in seconds, expressed in where PDV[i] is in units of time in seconds, expressed in
sufficiently fine resolution to convey meaningful quantitative sufficiently fine resolution to convey meaningful quantitative
information. For example, resolution of microseconds is usually information. For example, resolution of microseconds is usually
sufficient. sufficient.
6.1.3. Discussion and other details 6.1.3. Discussion and Other Details
This metric produces a sample of delay variation normalized to the This metric produces a sample of delay variation normalized to the
minimum delay of the sample. The resulting delay variation minimum delay of the sample. The resulting delay variation
distribution is independent of the sending sequence (although distribution is independent of the sending sequence (although
specific FiniteDelay values within the distribution may be specific FiniteDelay values within the distribution may be
correlated, depending on various stream parameters such as packet correlated, depending on various stream parameters such as packet
spacing). This metric is equivalent to the IP Packet Delay Variation spacing). This metric is equivalent to the IP Packet Delay Variation
parameter defined in [Y.1540]. parameter defined in [Y.1540].
6.1.4. Statistics: Mean, Variance, Skewness, Quantile 6.1.4. Statistics: Mean, Variance, Skewness, Quantile
skipping to change at page 21, line 28 skipping to change at page 22, line 8
--- ---
1 \ 2 1 \ 2
------- > (PDV[n] - MeanPDV) ------- > (PDV[n] - MeanPDV)
(N - 1) / (N - 1) /
--- ---
n = 1 n = 1
We define the skewness of PDV as follows: We define the skewness of PDV as follows:
Type-P-One-way-pdv-refmin-Skewness = SkewPDV = Type-P-One-way-pdv-refmin-Skewness = SkewPDV =
N N
--- 3 --- 3
\ / \ \ / \
> | PDV[n]- MeanPDV | > | PDV[n] - MeanPDV |
/ \ / / \ /
--- ---
n = 1 n = 1
----------------------------------- -----------------------------------
/ \ / \
| ( 3/2 ) | | ( 3/2 ) |
\ (N - 1) * VarPDV / \ (N - 1) * VarPDV /
(see Appendix X of [Y.1541] for additional background information). (See Appendix X of [Y.1541] for additional background information.)
We define the Quantile of the PDVRefMin sample as the value where the We define the quantile of the PDV sample as the value where the
specified fraction of singletons is less than the given value. specified fraction of singletons is less than the given value.
6.1.5. Composition Functions: 6.1.5. Composition Functions
This section gives two alternative composition functions. The This section gives two alternative composition functions. The
objective is to estimate a quantile of the complete path delay objective is to estimate a quantile of the complete path delay
variation distribution. The composed quantile will be estimated variation distribution. The composed quantile will be estimated
using information from the sub-path delay variation distributions. using information from the sub-path delay variation distributions.
6.1.5.1. Approximate Convolution 6.1.5.1. Approximate Convolution
The Type-P-Finite-One-way-Delay-<Sample>-Stream samples from each The Type-P-Finite-One-way-Delay-<Sample>-Stream samples from each
sub-path are summarized as a histogram with 1 ms bins representing sub-path are summarized as a histogram with 1-ms bins representing
the one-way delay distribution. the one-way delay distribution.
From [Stats], the distribution of the sum of independent random From [STATS], the distribution of the sum of independent random
variables can be derived using the relation: variables can be derived using the relation:
Type-P-Composite-One-way-pdv-refmin-quantile-a = Type-P-Composite-One-way-pdv-refmin-quantile-a =
. . . .
/ / / /
P(X + Y + Z <= a) = | | P(X <= a-y-z) * P(Y = y) * P(Z = z) dy dz P(X + Y + Z <= a) = | | P(X <= a - y - z) * P(Y = y) * P(Z = z) dy dz
/ / / /
` ` ` `
z y z y
Note that dy and dz indicate partial integration above, and that y
and z are the integration variables. Also, the probablility of an
outcome is indicated by the symbol P(outcome).
where X, Y, and Z are random variables representing the delay Note that dy and dz indicate partial integration above, and that y
variation distributions of the sub-paths of the complete path (in and z are the integration variables. Also, the probability of an
this case, there are three sub-paths), and a is the quantile of outcome is indicated by the symbol P(outcome), where X, Y, and Z are
interest. random variables representing the delay variation distributions of
the sub-paths of the complete path (in this case, there are three
sub-paths), and "a" is the quantile of interest.
This relation can be used to compose a quantile of interest for the This relation can be used to compose a quantile of interest for the
complete path from the sub-path delay distributions. The histograms complete path from the sub-path delay distributions. The histograms
with 1 ms bins are discrete approximations of the delay with 1-ms bins are discrete approximations of the delay
distributions. distributions.
6.1.5.2. Normal Power Approximation 6.1.5.2. Normal Power Approximation (NPA)
Type-P-One-way-Composite-pdv-refmin-NPA for the complete Source to Type-P-One-way-Composite-pdv-refmin-NPA for the complete source to
Destination path can be calculated by combining statistics of all the destination path can be calculated by combining the statistics of all
constituent sub-paths in the process described in [Y.1541] clause 8 the constituent sub-paths in the process described in [Y.1541],
and Appendix X. Clause 8 and Appendix X.
6.1.6. Statement of Conjecture and Assumptions 6.1.6. Statement of Conjecture and Assumptions
The delay distribution of a sufficiently large stream of packets The delay distribution of a sufficiently large stream of packets
measured on each sub-path during the interval [T, Tf] will be measured on each sub-path during the interval [T, Tf] will be
sufficiently stationary and the sub-path distributions themselves are sufficiently stationary, and the sub-path distributions themselves
sufficiently independent, so that summary information describing the are sufficiently independent, so that summary information describing
sub-path distributions can be combined to estimate the delay the sub-path distributions can be combined to estimate the delay
distribution of complete path. distribution of the complete path.
It is assumed that the one-way delay distributions of the sub-paths It is assumed that the one-way delay distributions of the sub-paths
and the complete path are continuous. and the complete path are continuous.
6.1.7. Justification of the Composition Function 6.1.7. Justification of the Composition Function
See the common section. See the common section (Section 3).
6.1.8. Sources of Deviation from the Ground Truth 6.1.8. Sources of Deviation from the Ground Truth
In addition to the common deviations, a few additional sources exist In addition to the common deviations, a few additional sources exist
here. For one, very tight distributions with range on the order of a here. For one, very tight distributions with ranges on the order of
few milliseconds are not accurately represented by a histogram with 1 a few milliseconds are not accurately represented by a histogram with
ms bins. This size was chosen assuming an implicit requirement on 1-ms bins. This size was chosen assuming an implicit requirement on
accuracy: errors of a few milliseconds are acceptable when assessing accuracy: errors of a few milliseconds are acceptable when assessing
a composed distribution quantile. a composed distribution quantile.
Also, summary statistics cannot describe the subtleties of an Also, summary statistics cannot describe the subtleties of an
empirical distribution exactly, especially when the distribution is empirical distribution exactly, especially when the distribution is
very different from a classical form. Any procedure that uses these very different from a classical form. Any procedure that uses these
statistics alone may incur error. statistics alone may incur error.
6.1.9. Specific cases where the conjecture might fail 6.1.9. Specific Cases where the Conjecture Might Fail
If the delay distributions of the sub-paths are somehow correlated, If the delay distributions of the sub-paths are somehow correlated,
then neither of these composition functions will be reliable then neither of these composition functions will be reliable
estimators of the complete path distribution. estimators of the complete path distribution.
In practice, sub-path delay distributions with extreme outliers have In practice, sub-path delay distributions with extreme outliers have
increased the error of the composed metric estimate. increased the error of the composed metric estimate.
6.1.10. Application of Measurement Methodology 6.1.10. Application of Measurement Methodology
See the common section. See the common section (Section 3).
7. Security Considerations 7. Security Considerations
7.1. Denial of Service Attacks 7.1. Denial-of-Service Attacks
This metric requires a stream of packets sent from one host (source) This metric requires a stream of packets sent from one host (source)
to another host (destination) through intervening networks. This to another host (destination) through intervening networks. This
method could be abused for denial of service attacks directed at the method could be abused for denial-of-service attacks directed at the
destination and/or the intervening network(s). destination and/or the intervening network(s).
Administrators of source, destination, and the intervening network(s) Administrators of source, destination, and intervening networks
should establish bilateral or multi-lateral agreements regarding the should establish bilateral or multilateral agreements regarding the
timing, size, and frequency of collection of sample metrics. Use of timing, size, and frequency of collection of sample metrics. Use of
this method in excess of the terms agreed between the participants this method in excess of the terms agreed upon between the
may be cause for immediate rejection or discard of packets or other participants may be cause for immediate rejection or discarding of
escalation procedures defined between the affected parties. packets, or other escalation procedures defined between the affected
parties.
7.2. User Data Confidentiality 7.2. User Data Confidentiality
Active use of this method generates packets for a sample, rather than Active use of this method generates packets for a sample, rather than
taking samples based on user data, and does not threaten user data taking samples based on user data, and does not threaten user data
confidentiality. Passive measurement MUST restrict attention to the confidentiality. Passive measurement MUST restrict attention to the
headers of interest. Since user payloads may be temporarily stored headers of interest. Since user payloads may be temporarily stored
for length analysis, suitable precautions MUST be taken to keep this for length analysis, suitable precautions MUST be taken to keep this
information safe and confidential. In most cases, a hashing function information safe and confidential. In most cases, a hashing function
will produce a value suitable for payload comparisons. will produce a value suitable for payload comparisons.
7.3. Interference with the metrics 7.3. Interference with the Metrics
It may be possible to identify that a certain packet or stream of It may be possible to identify that a certain packet or stream of
packets is part of a sample. With that knowledge at the destination packets is part of a sample. With that knowledge at the destination
and/or the intervening networks, it is possible to change the and/or the intervening networks, it is possible to change the
processing of the packets (e.g. increasing or decreasing delay) that processing of the packets (e.g., increasing or decreasing delay),
may distort the measured performance. It may also be possible to which may distort the measured performance. It may also be possible
generate additional packets that appear to be part of the sample to generate additional packets that appear to be part of the sample
metric. These additional packets are likely to perturb the results metric. These additional packets are likely to perturb the results
of the sample measurement. of the sample measurement.
To discourage the kind of interference mentioned above, packet To discourage the kind of interference mentioned above, packet
interference checks, such as cryptographic hash, may be used. interference checks, such as cryptographic hash, may be used.
8. IANA Considerations 8. IANA Considerations
Metrics defined in IETF are typically registered in the IANA IPPM Metrics defined in the IETF are typically registered in the IANA IPPM
METRICS REGISTRY as described in initial version of the registry Metrics Registry as described in the initial version of the registry
[RFC4148]. [RFC4148].
IANA is asked to register the following metrics in the IANA-IPPM- IANA has registered the following metrics in the
METRICS-REGISTRY-MIB: IANA-IPPM-METRICS-REGISTRY-MIB:
ietfFiniteOneWayDelayStream OBJECT-IDENTITY ietfFiniteOneWayDelayStream OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Finite-One-way-Delay-Stream" "Type-P-Finite-One-way-Delay-Stream"
REFERENCE REFERENCE "RFC 6049, Section 4.1."
"Reference "RFCyyyy, section 4.1." ::= { ianaIppmMetrics 71 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfFiniteOneWayDelayMean OBJECT-IDENTITY ietfFiniteOneWayDelayMean OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Finite-One-way-Delay-Mean" "Type-P-Finite-One-way-Delay-Mean"
REFERENCE REFERENCE "RFC 6049, Section 4.2."
"Reference "RFCyyyy, section 4.2." ::= { ianaIppmMetrics 72 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfCompositeOneWayDelayMean OBJECT-IDENTITY ietfCompositeOneWayDelayMean OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Finite-Composite-One-way-Delay-Mean" "Type-P-Finite-Composite-One-way-Delay-Mean"
REFERENCE REFERENCE "RFC 6049, Section 4.2.5."
"Reference "RFCyyyy, section 4.2.5." ::= { ianaIppmMetrics 73 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfFiniteOneWayDelayMinimum OBJECT-IDENTITY ietfFiniteOneWayDelayMinimum OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Finite-One-way-Delay-Minimum" "Type-P-Finite-One-way-Delay-Minimum"
REFERENCE REFERENCE "RFC 6049, Section 4.3.2."
"Reference "RFCyyyy, section 4.3.2." ::= { ianaIppmMetrics 74 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfCompositeOneWayDelayMinimum OBJECT-IDENTITY ietfCompositeOneWayDelayMinimum OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Finite-Composite-One-way-Delay-Minimum" "Type-P-Finite-Composite-One-way-Delay-Minimum"
REFERENCE REFERENCE "RFC 6049, Section 4.3."
"Reference "RFCyyyy, section 4.3." ::= { ianaIppmMetrics 75 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfOneWayPktLossEmpiricProb OBJECT-IDENTITY ietfOneWayPktLossEmpiricProb OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-One-way-Packet-Loss-Empirical-Probability" "Type-P-One-way-Packet-Loss-Empirical-Probability"
REFERENCE REFERENCE "RFC 6049, Section 5.1.4"
"Reference "RFCyyyy, section 5.1.4" ::= { ianaIppmMetrics 76 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfCompositeOneWayPktLossEmpiricProb OBJECT-IDENTITY ietfCompositeOneWayPktLossEmpiricProb OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Composite-One-way-Packet-Loss-Empirical-Probability" "Type-P-Composite-One-way-Packet-Loss-Empirical-Probability"
REFERENCE REFERENCE "RFC 6049, Section 5.1."
"Reference "RFCyyyy, section 5.1." ::= { ianaIppmMetrics 77 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfOneWayPdvRefminStream OBJECT-IDENTITY ietfOneWayPdvRefminStream OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-One-way-pdv-refmin-Stream" "Type-P-One-way-pdv-refmin-Stream"
REFERENCE REFERENCE "RFC 6049, Section 6.1."
"Reference "RFCyyyy, section 6.1." ::= { ianaIppmMetrics 78 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfOneWayPdvRefminMean OBJECT-IDENTITY ietfOneWayPdvRefminMean OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-One-way-pdv-refmin-Mean" "Type-P-One-way-pdv-refmin-Mean"
REFERENCE REFERENCE "RFC 6049, Section 6.1.4."
"Reference "RFCyyyy, section 6.1.4." ::= { ianaIppmMetrics 79 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfOneWayPdvRefminVariance OBJECT-IDENTITY ietfOneWayPdvRefminVariance OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-One-way-pdv-refmin-Variance" "Type-P-One-way-pdv-refmin-Variance"
REFERENCE REFERENCE "RFC 6049, Section 6.1.4."
"Reference "RFCyyyy, section 6.1.4." ::= { ianaIppmMetrics 80 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfOneWayPdvRefminSkewness OBJECT-IDENTITY ietfOneWayPdvRefminSkewness OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-One-way-pdv-refmin-Skewness" "Type-P-One-way-pdv-refmin-Skewness"
REFERENCE REFERENCE "RFC 6049, Section 6.1.4."
"Reference "RFCyyyy, section 6.1.4." ::= { ianaIppmMetrics 81 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfCompositeOneWayPdvRefminQtil OBJECT-IDENTITY ietfCompositeOneWayPdvRefminQtil OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-Composite-One-way-pdv-refmin-quantile-a" "Type-P-Composite-One-way-pdv-refmin-quantile-a"
REFERENCE REFERENCE "RFC 6049, Section 6.1.5.1."
"Reference "RFCyyyy, section 6.1.5.1." ::= { ianaIppmMetrics 82 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
ietfCompositeOneWayPdvRefminNPA OBJECT-IDENTITY ietfCompositeOneWayPdvRefminNPA OBJECT-IDENTITY
STATUS current STATUS current
DESCRIPTION DESCRIPTION
"Type-P-One-way-Composite-pdv-refmin-NPA" "Type-P-One-way-Composite-pdv-refmin-NPA"
REFERENCE REFERENCE "RFC 6049, Section 6.1.5.2."
"Reference "RFCyyyy, section 6.1.5.2." ::= { ianaIppmMetrics 83 }
-- RFC Ed.: replace yyyy with actual RFC number & remove this
note
::= { ianaIppmMetrics nn } -- IANA assigns nn
9. Contributors and Acknowledgements 9. Contributors and Acknowledgements
The following people have contributed useful ideas, suggestions, or The following people have contributed useful ideas, suggestions, or
the text of sections that have been incorporated into this memo: the text of sections that have been incorporated into this memo:
- Phil Chimento <vze275m9@verizon.net> - Phil Chimento <vze275m9@verizon.net>
- Reza Fardid <RFardid@cariden.com> - Reza Fardid <RFardid@cariden.com>
skipping to change at page 29, line 17 skipping to change at page 28, line 45
10.2. Informative References 10.2. Informative References
[RFC5474] Duffield, N., Chiou, D., Claise, B., Greenberg, A., [RFC5474] Duffield, N., Chiou, D., Claise, B., Greenberg, A.,
Grossglauser, M., and J. Rexford, "A Framework for Packet Grossglauser, M., and J. Rexford, "A Framework for Packet
Selection and Reporting", RFC 5474, March 2009. Selection and Reporting", RFC 5474, March 2009.
[RFC5481] Morton, A. and B. Claise, "Packet Delay Variation [RFC5481] Morton, A. and B. Claise, "Packet Delay Variation
Applicability Statement", RFC 5481, March 2009. Applicability Statement", RFC 5481, March 2009.
[Stats] McGraw-Hill NY NY, "Introduction to the Theory of [RFC5644] Stephan, E., Liang, L., and A. Morton, "IP Performance
Statistics, 3rd Edition,", 1974. Metrics (IPPM): Spatial and Multicast", RFC 5644,
October 2009.
[STATS] Mood, A., Graybill, F., and D. Boes, "Introduction to the
Theory of Statistics, 3rd Edition", McGraw-Hill, New York,
NY, 1974.
[Y.1540] ITU-T Recommendation Y.1540, "Internet protocol data [Y.1540] ITU-T Recommendation Y.1540, "Internet protocol data
communication service - IP packet transfer and communication service - IP packet transfer and
availability performance parameters", November 2007. availability performance parameters", November 2007.
[Y.1541] ITU-T Recommendation Y.1541, "Network Performance [Y.1541] ITU-T Recommendation Y.1541, "Network Performance
Objectives for IP-based Services", February 2006. Objectives for IP-based Services", February 2006.
Index
?
??? 14
Authors' Addresses Authors' Addresses
Al Morton Al Morton
AT&T Labs AT&T Labs
200 Laurel Avenue South 200 Laurel Avenue South
Middletown,, NJ 07748 Middletown, NJ 07748
USA USA
Phone: +1 732 420 1571 Phone: +1 732 420 1571
Fax: +1 732 368 1192 Fax: +1 732 368 1192
Email: acmorton@att.com EMail: acmorton@att.com
URI: http://home.comcast.net/~acmacm/ URI: http://home.comcast.net/~acmacm/
Emile Stephan
France Telecom Division R&D Stephan Emile
France Telecom Orange
2 avenue Pierre Marzin 2 avenue Pierre Marzin
Lannion, F-22307 Lannion, F-22307
France France
Phone: EMail: emile.stephan@orange-ftgroup.com
Fax: +33 2 96 05 18 52
Email: emile.stephan@orange-ftgroup.com
URI:
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