draft-ietf-ippm-framework-compagg-05.txt   draft-ietf-ippm-framework-compagg-06.txt 
Network Working Group A. Morton, Ed. Network Working Group A. Morton, Ed.
Internet-Draft AT&T Labs Internet-Draft AT&T Labs
Intended status: Informational S. Van den Berghe, Ed. Intended status: Informational S. Van den Berghe, Ed.
Expires: May 8, 2008 Ghent University - IBBT Expires: August 8, 2008 Ghent University - IBBT
November 5, 2007 February 5, 2008
Framework for Metric Composition Framework for Metric Composition
draft-ietf-ippm-framework-compagg-05 draft-ietf-ippm-framework-compagg-06
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Copyright Notice Copyright Notice
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Abstract Abstract
This memo describes a framework for composing and aggregating metrics This memo describes a framework for composing and aggregating metrics
(both in time and in space) defined by RFC 2330 and developed by the (both in time and in space) defined by RFC 2330 and developed by the
IPPM working group. The framework describes the generic composition IPPM working group. The framework describes the generic composition
and aggregation mechanisms. It provides a basis for additional and aggregation mechanisms. It provides a basis for additional
documents that implement this framework for detailed, and practically documents that implement this framework for detailed, and practically
useful, compositions and aggregations of metrics. useful, compositions and aggregations of metrics.
Requirements Language Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119]. document are to be interpreted as described in RFC 2119 [RFC2119].
Table of Contents Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1. Motivation . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1.1. Reducing Measurement Overhead . . . . . . . . . . . . 3 1.1.1. Reducing Measurement Overhead . . . . . . . . . . . . 4
1.1.2. Measurement Re-use . . . . . . . . . . . . . . . . . . 4 1.1.2. Measurement Re-use . . . . . . . . . . . . . . . . . . 5
1.1.3. Data Reduction and Consolidation . . . . . . . . . . . 4 1.1.3. Data Reduction and Consolidation . . . . . . . . . . . 5
1.1.4. Implications on Measurement Design and Reporting . . . 5 1.1.4. Implications on Measurement Design and Reporting . . . 6
2. Purpose and Scope . . . . . . . . . . . . . . . . . . . . . . 5 2. Purpose and Scope . . . . . . . . . . . . . . . . . . . . . . 6
3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 5 3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1. Measurement Point . . . . . . . . . . . . . . . . . . . . 5 3.1. Measurement Point . . . . . . . . . . . . . . . . . . . . 6
3.2. Complete path . . . . . . . . . . . . . . . . . . . . . . 6 3.2. Complete Path . . . . . . . . . . . . . . . . . . . . . . 7
3.3. Complete path metric . . . . . . . . . . . . . . . . . . . 6 3.3. Complete Path Metric . . . . . . . . . . . . . . . . . . . 7
3.4. Composed Metric . . . . . . . . . . . . . . . . . . . . . 6 3.4. Complete Time Interval . . . . . . . . . . . . . . . . . . 7
3.5. Composition Function . . . . . . . . . . . . . . . . . . . 6 3.5. Composed Metric . . . . . . . . . . . . . . . . . . . . . 7
3.6. Index . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.6. Composition Function . . . . . . . . . . . . . . . . . . . 7
3.7. Ground Truth . . . . . . . . . . . . . . . . . . . . . . . 6 3.7. Index . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.8. Sub-interval . . . . . . . . . . . . . . . . . . . . . . . 6 3.8. Ground Truth . . . . . . . . . . . . . . . . . . . . . . . 8
3.9. Sub-path . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.9. Sub-interval . . . . . . . . . . . . . . . . . . . . . . . 8
3.10. Sub-path metrics . . . . . . . . . . . . . . . . . . . . . 7 3.10. Sub-path . . . . . . . . . . . . . . . . . . . . . . . . . 8
4. Description of Metric Types . . . . . . . . . . . . . . . . . 7 3.11. Sub-path Metrics . . . . . . . . . . . . . . . . . . . . . 8
4.1. Temporal Aggregation Description . . . . . . . . . . . . . 7 4. Description of Metric Types . . . . . . . . . . . . . . . . . 8
4.2. Spatial Aggregation Description . . . . . . . . . . . . . 8 4.1. Temporal Aggregation Description . . . . . . . . . . . . . 8
4.3. Spatial Composition Description . . . . . . . . . . . . . 8 4.2. Spatial Aggregation Description . . . . . . . . . . . . . 9
4.4. Help Metrics . . . . . . . . . . . . . . . . . . . . . . . 9 4.3. Spatial Composition Description . . . . . . . . . . . . . 10
4.5. Higher Order Composition . . . . . . . . . . . . . . . . . 9 4.4. Help Metrics . . . . . . . . . . . . . . . . . . . . . . . 10
5. Requirements for Composed Metrics . . . . . . . . . . . . . . 9 4.5. Higher Order Composition . . . . . . . . . . . . . . . . . 10
6. Guidelines for Defining Composed Metrics . . . . . . . . . . . 10 5. Requirements for Composed Metrics . . . . . . . . . . . . . . 11
6.1. Ground Truth: Comparison with other IPPM Metrics . . . . . 10 6. Guidelines for Defining Composed Metrics . . . . . . . . . . . 12
6.1.1. Ground Truth for Temporal Aggregation . . . . . . . . 12 6.1. Ground Truth: Comparison with other IPPM Metrics . . . . . 12
6.1.2. Ground Truth for Spatial Aggregation . . . . . . . . . 13 6.1.1. Ground Truth for Temporal Aggregation . . . . . . . . 14
6.2. Deviation from the Ground Truth . . . . . . . . . . . . . 13 6.1.2. Ground Truth for Spatial Aggregation . . . . . . . . . 14
6.3. Incomplete Information . . . . . . . . . . . . . . . . . . 13 6.2. Deviation from the Ground Truth . . . . . . . . . . . . . 14
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13 6.3. Incomplete Information . . . . . . . . . . . . . . . . . . 14
8. Security Considerations . . . . . . . . . . . . . . . . . . . 14 6.4. Time Varying Metrics . . . . . . . . . . . . . . . . . . . 15
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 14 7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 15
10. References . . . . . . . . . . . . . . . . . . . . . . . . . . 14 8. Security Considerations . . . . . . . . . . . . . . . . . . . 15
10.1. Normative References . . . . . . . . . . . . . . . . . . . 14 9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 15
10.2. Informative References . . . . . . . . . . . . . . . . . . 14 10. References . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 14 10.1. Normative References . . . . . . . . . . . . . . . . . . . 15
Intellectual Property and Copyright Statements . . . . . . . . . . 16 10.2. Informative References . . . . . . . . . . . . . . . . . . 16
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 16
Intellectual Property and Copyright Statements . . . . . . . . . . 17
1. Introduction 1. Introduction
The IPPM framework [RFC2330] describes two forms of metric The IPPM framework [RFC2330] describes two forms of metric
composition, spatial and temporal. Also, the text suggests that the composition, spatial and temporal. Also, the text suggests that the
concepts of the analytical framework (or A-frame) would help to concepts of the analytical framework (or A-frame) would help to
develop useful relationships to derive the composed metrics from real develop useful relationships to derive the composed metrics from real
metrics. The effectiveness of composed metrics is dependent on their metrics. The effectiveness of composed metrics is dependent on their
usefulness in analysis and applicability to practical measurement usefulness in analysis and applicability to practical measurement
circumstances. circumstances.
This memo expands on the notion of composition, and provides a This memo expands on the notion of composition, and provides a
detailed framework for several classes of metrics that were mentioned detailed framework for several classes of metrics that were mentioned
in the original IPPM framework. The classes include temporal in the original IPPM framework. The classes include temporal
aggregation, spatial aggregation, and spatial composition. aggregation, spatial aggregation, and spatial composition.
1.1. Motivation 1.1. Motivation
Network operators have deployed measurement systems to serve many Network operators have deployed measurement systems to serve many
purposes, including performance monitoring, maintenance support, purposes, including performance monitoring, maintenance support,
network engineering, and customer reporting. The collection of network engineering, and reporting performance to customers. The
elementary measurements alone is not enough to understand a network's collection of elementary measurements alone is not enough to
behaviour. In general, measurements need to be post-processed to understand a network's behaviour. In general, measurements need to
present the most relevant information for each purpose. The first be post-processed to present the most relevant information for each
step is often a process of "composition" of single measurements or purpose. The first step is often a process of "composition" of
measurement sets into other forms. Composition and aggregation single measurements or measurement sets into other forms.
present several more post-processing opportunities to the network Composition and aggregation present several more post-processing
operator, and we describe the key motivations below. opportunities to the network operator, and we describe the key
motivations below.
1.1.1. Reducing Measurement Overhead 1.1.1. Reducing Measurement Overhead
A network's measurement possibilities scale upward with the square of A network's measurement possibilities scale upward with the square of
the number of nodes. But each measurement implies overhead, in terms the number of nodes. But each measurement implies overhead, in terms
of the storage for the results, the traffic on the network (assuming of the storage for the results, the traffic on the network (assuming
active methods), and the OA&M for the measurement system itself. In active methods), and the operation and administration of the
a large network, it is impossible to perform measurements from each measurement system itself. In a large network, it is impossible to
node to all others. perform measurements from each node to all others.
An individual network operator should be able to organize their An individual network operator should be able to organize their
measurement paths along the lines of physical topology, or routing measurement paths along the lines of physical topology, or routing
areas/Autonomous Systems, and thus minimize dependencies and overlap areas/Autonomous Systems, and thus minimize dependencies and overlap
between different measurement paths. This way, the sheer number of between different measurement paths. This way, the sheer number of
measurements can be reduced, as long as the operator has a set of measurements can be reduced, as long as the operator has a set of
methods to estimate performance between any particular nodes when methods to estimate performance between any particular pair of nodes
needed. when needed.
Composition and aggregation play a key role when the path of interest Composition and aggregation play a key role when the path of interest
spans multiple networks, and where each operator conducts their own spans multiple networks, and where each operator conducts their own
measurements. Here, the complete path performance may be estimated measurements. Here, the complete path performance may be estimated
from measurements on the component parts. from measurements on the component parts.
Operators that take advantage of the composition and aggregation Operators that take advantage of the composition and aggregation
methods recognize that the estimates may exhibit some additional methods recognize that the estimates may exhibit some additional
error beyond that inherent in the measurements themselves, and so error beyond that inherent in the measurements themselves, and so
they are making a trade-off to achieve reasonable measurement system they are making a trade-off to achieve reasonable measurement system
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If a network measurement system operator anticipates needing to If a network measurement system operator anticipates needing to
produce overall metrics by composition, then it is prudent to keep produce overall metrics by composition, then it is prudent to keep
that requirement in mind when considering the measurement design and that requirement in mind when considering the measurement design and
sampling plan. Also, certain summary statistics are more conducive sampling plan. Also, certain summary statistics are more conducive
to composition than others, and this figures prominently in the to composition than others, and this figures prominently in the
design of measurements and when reporting the results. design of measurements and when reporting the results.
2. Purpose and Scope 2. Purpose and Scope
The purpose of this memo is provide a common framework for the The purpose of this memo is provide a common framework for the
various classes of metrics based on composition of primary metrics. various classes of metrics that are composed from primary metrics.
The scope is limited to the definitions of metrics that are composed The scope is limited to the definitions of metrics that are composed
from primary metrics using a deterministic function. Key information from primary metrics using a deterministic function. Key information
about each metric, such as the assumptions under which the about each composed metric, such as the assumptions under which the
relationship holds and possible sources of error/circumstances where relationship holds and possible sources of error/circumstances where
the composition may fail, are included. the composition may fail, are included.
At this time, the scope of effort is limited to the metrics for At this time, the scope of effort is limited to composed metrics for
packet loss, delay, and delay variation. Composition of packet packet loss, delay, and delay variation. Composition of packet
reordering metrics is considered a research topic at the time this reordering metrics is considered a research topic at the time this
memo was prepared, and beyond its scope. memo was prepared, and beyond its scope.
This memo will retain the terminology of the IPPM Framework This memo will retain the terminology of the IPPM Framework
[RFC2330]as much as possible, but will extend the terminology when [RFC2330]as much as possible, but will extend the terminology when
necessary. It is assumed that the reader is familiar with the necessary. It is assumed that the reader is familiar with the
concepts introduced in [RFC2330], as they will not be repeated here. concepts introduced in [RFC2330], as they will not be repeated here.
3. Terminology 3. Terminology
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3.1. Measurement Point 3.1. Measurement Point
The logical or physical location where packet observations are made. The logical or physical location where packet observations are made.
The term Measurement Point is synonymous with the term "observation The term Measurement Point is synonymous with the term "observation
position" used in [RFC2330] when describing the notion of wire time. position" used in [RFC2330] when describing the notion of wire time.
A measurement point may be at the boundary between a host and an A measurement point may be at the boundary between a host and an
adjacent link (physical), or it may be within a host (logical) that adjacent link (physical), or it may be within a host (logical) that
performs measurements where the difference between host time and wire performs measurements where the difference between host time and wire
time is understood. time is understood.
3.2. Complete path 3.2. Complete Path
The complete path is the true path that a packet would follow as it The complete path is the actual path that a packet would follow as it
traverses from the packet's Source to its Destination. travels from the packet's Source to its Destination.
3.3. Complete path metric 3.3. Complete Path Metric
The complete path metric is the Source to Destination metric that a The complete path metric is the Source to Destination metric that a
composed metric is estimating. A complete path metric represents the composed metric attempts to estimate. A complete path metric
ground-truth for a composed metric. represents the ground-truth for a composed metric.
3.4. Composed Metric 3.4. Complete Time Interval
The complete time interval is comprised of two or more contiguous
sub-intervals, and is the interval whose performance will be
estimated through temporal aggregation.
3.5. Composed Metric
A composed metric is an estimate of an actual metric describing the A composed metric is an estimate of an actual metric describing the
performance of a path over some time interval. A composed metric is performance of a path over some time interval. A composed metric is
derived from other metrics by applying a deterministic process or derived from other metrics by applying a deterministic process or
function (e.g., a composition function). The process may use metrics function (e.g., a composition function). The process may use metrics
that are identical to the metric being composed, or metrics that are that are identical to the metric being composed, or metrics that are
dissimilar, or some combination of both types. dissimilar, or some combination of both types.
3.5. Composition Function 3.6. Composition Function
A composition function is a deterministic process applied to A composition function is a deterministic process applied to
individual metrics to derive another metric (such as a Composed individual metrics to derive another metric (such as a Composed
metric). metric).
3.6. Index 3.7. Index
An Index is a composed metric for which the output value range has An Index is a metric for which the output value range has been
been selected for convenience or clarity, and the behavior of which selected for convenience or clarity, and the behavior of which is
is selected to support ease of understanding. The composition selected to support ease of understanding. The deterministic
function for an index is often developed after the index range and function for an index is often developed after the index range and
index behavior have been determined. Examples include the R factor, index behavior have been determined. Examples include the Effective
as described in [G.107]. Equipment Impairment Factor as described in section 3.5 of ITU-T
Recommendation [G.107].
3.7. Ground Truth >>> Comment: Perhaps the definition of an Index should move to the
PMOL Framework?
3.8. Ground Truth
As applied here, the notion of ground truth is defined as the actual As applied here, the notion of ground truth is defined as the actual
performance of a network path over some time interval. The ground performance of a network path over some time interval. The ground
truth is metric based on the (unavailable) measurement that a truth is a metric on the (unavailable) packet transfer information
composed metric seeks to estimate. for the desired path and time interval that a composed metric seeks
to estimate.
3.8. Sub-interval 3.9. Sub-interval
A Sub-interval is a time interval that is included in another A Sub-interval is a time interval that is included in another
interval. interval.
3.9. Sub-path 3.10. Sub-path
A Sub-path is a portion of the complete path where at least the Sub- A Sub-path is a portion of the complete path where at least the Sub-
path Source and Destination hosts are constituents of the complete path Source and Destination hosts are constituents of the complete
path. We say that this sub-path is "involved" in the complete path. path. We say that this sub-path is "involved" in the complete path.
3.10. Sub-path metrics 3.11. Sub-path Metrics
A sub-path path metric is an element of the process to derive a A sub-path path metric is an element of the process to derive a
Composite metric, quantifying some aspect of the performance a Composite metric, quantifying some aspect of the performance a
particular sub-path from its Source to Destination. particular sub-path from its Source to Destination.
4. Description of Metric Types 4. Description of Metric Types
This section defines the various classes of Composition. There are This section defines the various classes of Composition. There are
two classes more accurately described as aggregation over time and two classes more accurately described as aggregation over time and
space, and the third involves concatenation in space. space, and the third involves concatenation in space.
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consecutive 5-minute minima. consecutive 5-minute minima.
The main reason for doing time aggregation is to reduce the amount of The main reason for doing time aggregation is to reduce the amount of
data that has to be stored, and make the visualization/spotting of data that has to be stored, and make the visualization/spotting of
regular cycles and/or growing or decreasing trends easier. Another regular cycles and/or growing or decreasing trends easier. Another
useful application is to detect anomalies or abnormal changes in the useful application is to detect anomalies or abnormal changes in the
network characteristics. network characteristics.
In RFC 2330, the term "temporal composition" is introduced and In RFC 2330, the term "temporal composition" is introduced and
differs from temporal aggregation in that it refers to methodologies differs from temporal aggregation in that it refers to methodologies
to predict future metrics on the basis of past observations, to predict future metrics on the basis of past observations (of the
exploiting the time correlation that certain metrics can exhibit. We same metrics), exploiting the time correlation that certain metrics
do not consider this type of composition here. can exhibit. We do not consider this type of composition here.
>>>>>>>>Comment: Why no forecasting? This was apparently a limit on >>>>>>>>Comment: Why no forecasting? This was apparently a limit on
the Geant2 project, but may not apply here. the Geant2 project, but may not apply here.
4.2. Spatial Aggregation Description 4.2. Spatial Aggregation Description
Aggregation in space is defined as the combination of metrics of the Aggregation in space is defined as the combination of metrics of the
same type and different scope, in order to estimate the overall same type and different scope, in order to estimate the overall
performance of a larger domain. This combination may involve performance of a larger domain. This combination may involve
weighing the contributions of the input metrics. weighing the contributions of the input metrics.
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Note that there may be small gaps in measurement coverage, likewise Note that there may be small gaps in measurement coverage, likewise
there may be small overlaps (e.g., the link where test equipment there may be small overlaps (e.g., the link where test equipment
connects to the network). connects to the network).
One key difference from examples of aggregation in space is that all One key difference from examples of aggregation in space is that all
sub-paths contribute equally to the composed metric, independent of sub-paths contribute equally to the composed metric, independent of
the traffic load present. the traffic load present.
4.4. Help Metrics 4.4. Help Metrics
Finally, note that in practice there is often the need of extracting In practice there is often the need to compute a new metric using one
a new metric making some computation over one or more metrics with or more metrics with the same spatial and time scope. For example,
the same spatial and time scope. For example, the composed metric the metric rtt_sample_variance may be computed from two different
rtt_sample_variance may be composed from two different metrics: the metrics: the help metrics rtt_square_sum and the rtt_sum. The
help metric rtt_square_sum and the statistical metric rtt_sum. This process of using help metrics is a simple calculation and not an
operation is however more a simple calculation and not an aggregation aggregation or a concatenation, and will not be investigated further
or a concatenation, and we'll not investigate it further in this in this memo.
memo.
4.5. Higher Order Composition 4.5. Higher Order Composition
Composed metrics might themselves be subject to further steps of Composed metrics might themselves be subject to further steps of
composition or aggregation. An example would be a the delay of a composition or aggregation. An example would be the delay of a
maximal domain obtained through the spatial composition of several maximal domain obtained through the spatial composition of several
composed end-to-end delays (obtained through spatial composition). composed delays for each domain in the maximal domain (obtained
All requirements for first order composition metrics apply to higher through spatial composition). All requirements for first order
order composition. composition metrics apply to higher order composition.
>>>>> Comment Response: are more examples needed here? An example using temporal aggregation: twelve 5-minute metrics are
aggregated to estimate the performance over an hour. The seconds
step of aggregation would take 24 hourly metrics and estimate the
performance over a day.
5. Requirements for Composed Metrics 5. Requirements for Composed Metrics
The definitions for all composed metrics MUST include sections to The definitions for all composed metrics MUST include sections to
treat the following topics. treat the following topics.
The description of each metric will clearly state: The description of each metric will clearly state:
1. the definition (and statistic, where appropriate); 1. the definition (and statistic, where appropriate);
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o Requires precisely synchronized measurement time intervals in all o Requires precisely synchronized measurement time intervals in all
component metrics, or loosely synchronized, or no timing component metrics, or loosely synchronized, or no timing
requirements. requirements.
o Requires assumption of component metric independence w.r.t. the o Requires assumption of component metric independence w.r.t. the
metric being defined/composed, or other assumptions. metric being defined/composed, or other assumptions.
o Has known sources of inaccuracy/error, and identifies the sources. o Has known sources of inaccuracy/error, and identifies the sources.
If one or more components of the composition process are encumbered
by Intellectual Property Rights (IPR), then the resulting Composed
Metrics may be encumbered as well. See BCP 79 [RFC3979] for IETF
policies on IPR disclosure.
6. Guidelines for Defining Composed Metrics 6. Guidelines for Defining Composed Metrics
6.1. Ground Truth: Comparison with other IPPM Metrics 6.1. Ground Truth: Comparison with other IPPM Metrics
Figure 1 illustrates the process to derive a metric using spatial Figure 1 illustrates the process to derive a metric using spatial
composition, and compares the composed metric to other IPPM metrics. composition, and compares the composed metric to other IPPM metrics.
Metrics <M1, M2, M3> describe the performance of sub-paths between Metrics <M1, M2, M3> describe the performance of sub-paths between
the Source and Destination of interest during time interval <T, Tf>. the Source and Destination of interest during time interval <T, Tf>.
These metrics are the inputs for a Composition Function that produces These metrics are the inputs for a Composition Function that produces
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small as possible. small as possible.
The description of the metric composition MUST include an section The description of the metric composition MUST include an section
identifying the deviation from the ground truth. identifying the deviation from the ground truth.
6.3. Incomplete Information 6.3. Incomplete Information
In practice, when measurements cannot be initiated on a sub-path or In practice, when measurements cannot be initiated on a sub-path or
during a particular measurement interval (and perhaps the measurement during a particular measurement interval (and perhaps the measurement
system gives up during the test interval), then there will not be a system gives up during the test interval), then there will not be a
value for the subpath reported, and the result SHOULD be recorded as value for the sub-path reported, and the result SHOULD be recorded as
"undefined". "undefined".
6.4. Time Varying Metrics
The measured values of many metrics depend on time-variant factors,
such as the level of network traffic on the source to destination
path. Traffic levels often exhibit diurnal (or daily) variation, but
a 24 hour measurement interval would obscure it. Temporal
Aggregation of hourly results to estimate the daily metric would have
the same effect, and so the same cautions are warranted.
Some metrics are predominantly* time-invariant, such as the actual
minimum one-way delay of fixed path, and therefore temporal
aggregation does not obscure the results as long as the path is
stable. However, paths do vary, and sometimes on less predictable
time intervals than traffic variations. (* Note - It is recognized
that propagation delay on transmission facilities may have diurnal,
seasonal, and even longer-term variations.)
7. IANA Considerations 7. IANA Considerations
This document makes no request of IANA. This document makes no request of IANA.
Note to RFC Editor: this section may be removed on publication as an Note to RFC Editor: this section may be removed on publication as an
RFC. RFC.
8. Security Considerations 8. Security Considerations
The security considerations that apply to any active measurement of The security considerations that apply to any active measurement of
live networks are relevant here as well. See [RFC4656]. live networks are relevant here as well. See [RFC4656].
9. Acknowledgements 9. Acknowledgements
The authors would like to thank Maurizio Molina, Andy Van Maele, The authors would like to thank Maurizio Molina, Andy Van Maele,
Andreas Haneman, Igor Velimirovic, Andreas Solberg, Athanassios Andreas Haneman, Igor Velimirovic, Andreas Solberg, Athanassios
Liakopulos, David Schitz, Nicolas Simar and the Geant2 Project. We Liakopulos, David Schitz, Nicolas Simar and the Geant2 Project. We
also acknowledge comments and suggestions from Phil Chimento, Emile also acknowledge comments and suggestions from Phil Chimento, Emile
Stephan, Lei Liang, Stephen Wolff, and Alan Clark. Stephan, Lei Liang, Stephen Wolff, Reza Fardid, Loki Jorgenson, and
Alan Clark.
10. References 10. References
10.1. Normative References 10.1. Normative References
[I-D.ietf-ippm-multimetrics] [I-D.ietf-ippm-multimetrics]
Stephan, E., "IP Performance Metrics (IPPM) for spatial Stephan, E., Liang, L., and A. Morton, "IP Performance
and multicast", draft-ietf-ippm-multimetrics-04 (work in Metrics (IPPM) for spatial and multicast",
progress), July 2007. draft-ietf-ippm-multimetrics-05 (work in progress),
November 2007.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997. Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis, [RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis,
"Framework for IP Performance Metrics", RFC 2330, "Framework for IP Performance Metrics", RFC 2330,
May 1998. May 1998.
[RFC3979] Bradner, S., "Intellectual Property Rights in IETF
Technology", BCP 79, RFC 3979, March 2005.
[RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M. [RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M.
Zekauskas, "A One-way Active Measurement Protocol Zekauskas, "A One-way Active Measurement Protocol
(OWAMP)", RFC 4656, September 2006. (OWAMP)", RFC 4656, September 2006.
10.2. Informative References 10.2. Informative References
[G.107] ITU-T Recommendation G.107, ""The E-model, a computational [G.107] ITU-T Recommendation G.107, ""The E-model, a computational
model for use in transmission planning"", March 2005. model for use in transmission planning"", March 2005.
Authors' Addresses Authors' Addresses
skipping to change at page 16, line 7 skipping to change at page 17, line 7
G. Crommenlaan 8 bus 201 G. Crommenlaan 8 bus 201
Gent 9050 Gent 9050
Belgium Belgium
Phone: +32 9 331 49 73 Phone: +32 9 331 49 73
Email: steven.vandenberghe@intec.ugent.be Email: steven.vandenberghe@intec.ugent.be
URI: http://www.ibcn.intec.ugent.be URI: http://www.ibcn.intec.ugent.be
Full Copyright Statement Full Copyright Statement
Copyright (C) The IETF Trust (2007). Copyright (C) The IETF Trust (2008).
This document is subject to the rights, licenses and restrictions This document is subject to the rights, licenses and restrictions
contained in BCP 78, and except as set forth therein, the authors contained in BCP 78, and except as set forth therein, the authors
retain all their rights. retain all their rights.
This document and the information contained herein are provided on an This document and the information contained herein are provided on an
"AS IS" basis and THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS "AS IS" basis and THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS
OR IS SPONSORED BY (IF ANY), THE INTERNET SOCIETY, THE IETF TRUST AND OR IS SPONSORED BY (IF ANY), THE INTERNET SOCIETY, THE IETF TRUST AND
THE INTERNET ENGINEERING TASK FORCE DISCLAIM ALL WARRANTIES, EXPRESS THE INTERNET ENGINEERING TASK FORCE DISCLAIM ALL WARRANTIES, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF
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