Network Working Group A. Clark
Internet-Draft Telchemy Incorporated
Intended status: BCP B. Claise
Expires: April 29, 2010 Cisco Systems, Inc.
October 26, 2009
Framework for Performance Metric Development
draft-ietf-pmol-metrics-framework-03
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Abstract
This document describes a framework and a process for developing
performance metrics for IP-based applications that operate over
reliable or datagram transport protocols, and that can be used to
characterize traffic on live networks and services. The framework
refers to a Performance Metrics Entity, or PM Entity, which may in
future be a working group or directorate or a combination of these
two.
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].
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Table of Contents
1. TO DO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1. Background and Motivation . . . . . . . . . . . . . . . . 4
2.2. Organization of this document . . . . . . . . . . . . . . 5
3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 6
3.1. Quality of Service . . . . . . . . . . . . . . . . . . . . 6
3.2. Application Performance Metric . . . . . . . . . . . . . . 6
3.3. Quality of Experience . . . . . . . . . . . . . . . . . . 6
4. Purpose and Scope . . . . . . . . . . . . . . . . . . . . . . 6
5. QoS versus Application Performance Metrics versus QoE . . . . 7
6. Metrics Development . . . . . . . . . . . . . . . . . . . . . 7
6.1. Identifying and Categorizing the Audience . . . . . . . . 7
6.2. Definitions of a Metric . . . . . . . . . . . . . . . . . 8
6.3. Computed Metrics . . . . . . . . . . . . . . . . . . . . . 9
6.3.1. Composed Metrics . . . . . . . . . . . . . . . . . . . 9
6.3.2. Index (from compagg) . . . . . . . . . . . . . . . . . 10
6.4. Metric Specification . . . . . . . . . . . . . . . . . . . 10
6.4.1. Outline . . . . . . . . . . . . . . . . . . . . . . . 11
6.4.2. Normative parts of metric definition . . . . . . . . . 11
6.4.3. Informative parts of metric definition . . . . . . . . 12
6.4.4. Metric Definition Template . . . . . . . . . . . . . . 13
6.4.5. Example: Burst Packet Loss Frequency . . . . . . . . . 14
6.5. Dependencies . . . . . . . . . . . . . . . . . . . . . . . 15
6.5.1. Timing accuracy . . . . . . . . . . . . . . . . . . . 15
6.5.2. Dependencies of metric definitions on related
events or metrics . . . . . . . . . . . . . . . . . . 15
6.5.3. Relationship between application performance and
lower layer metrics . . . . . . . . . . . . . . . . . 15
6.5.4. Middlebox presence . . . . . . . . . . . . . . . . . . 16
6.6. Organization of Results . . . . . . . . . . . . . . . . . 16
6.7. Parameters, the variables of a metric . . . . . . . . . . 16
7. Performance Metric Development Process . . . . . . . . . . . . 17
7.1. New Proposals for Metrics . . . . . . . . . . . . . . . . 17
7.2. Reviewing Metrics . . . . . . . . . . . . . . . . . . . . 17
7.3. Proposal Approval . . . . . . . . . . . . . . . . . . . . 18
7.4. PM Entity Interaction with other WGs . . . . . . . . . . . 19
7.5. Standards Track Performance Metrics . . . . . . . . . . . 19
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 19
9. Security Considerations . . . . . . . . . . . . . . . . . . . 19
10. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 20
11. References . . . . . . . . . . . . . . . . . . . . . . . . . . 20
11.1. Normative References . . . . . . . . . . . . . . . . . . . 20
11.2. Informative References . . . . . . . . . . . . . . . . . . 20
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 21
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1. TO DO
o Multiple EDITOR'S NOTES throughout the document
o Should we refer to ITU G1010 for application performance metrics?
o Do we want a definition for Performance Metric Entity?
2. Introduction
Many networking technologies, applications, or services, are
distributed in nature, and their performance may be impacted by IP
impairments, server capacity, congestion and other factors. It is
important to measure the performance of applications and services to
ensure that quality objectives are being met and to support problem
diagnosis. Standardized metrics help to ensure that performance
measurement is implemented consistently and to facilitate
interpretation and comparison.
There are at least three phases in the development of performance
standards. They are:
1. Definition of a Performance Metric and its units of measure
2. Specification of a Method of Measurement
3. Specification of the Reporting Format
During the development of metrics, it is often useful to define
performance objectives and expected value ranges. However, this is
not defined as part of the metric specification.
This document refers to a Performance Metrics Entity, or PM Entity,
which may in future be a working group or directorate or a
combination of these two.
2.1. Background and Motivation
Although the IETF has two active Working Groups dedicated to the
development of performance metrics, they each have strict limitations
in their charters:
- The Benchmarking Methodology Working Group has addressed a range of
networking technologies and protocols in their long history (such as
IEEE 802.3, ATM, Frame Relay, and Routing Protocols), but the charter
strictly limits their performance characterizations to the laboratory
environment.
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- The IP Performance Metrics (IPPM) Working Group has developed a set
of standard metrics that can be applied to the quality, performance,
and reliability of Internet data delivery services. The IPPM metrics
development is applicable to live IP networks, but it is specifically
prohibited from developing metrics that characterize traffic at upper
layers, such as a VoIP stream.
A BOF held at IETF-69 introduced the IETF community to the
possibility of a generalized activity to define standardized
performance metrics. The existence of a growing list of Internet-
Drafts on performance metrics (with community interest in
development, but in un-chartered areas) illustrates the need for
additional performance work. The majority of people present at the
BOF supported the proposition that IETF should be working in these
areas, and no one objected to any of the proposals.
The IETF does have current and completed activities related to the
reporting of application performance metrics: for example the Real-
time Application Quality-of-Service Monitoring (RAQMON) Framework RFC
4710 [RFC4710], which extends the remote network monitoring (RMON)
family of specifications to allow real-time quality-of-service (QoS)
monitoring of various applications that run on devices such as IP
phones, pagers, Instant Messaging clients, mobile phones, and various
other handheld computing devices.
The IETF is also actively involved in the development of reliable
transport protocols which would affect the relationship between IP
performance and application performance.
EDITOR'S NOTE: I'm not sure what the previous sentence refers to?
Thus there is a gap in the currently chartered coverage of IETF WGs:
development of performance metrics for non-IP-layer protocols that
can be used to characterize performance on live networks.
EDITOR'S NOTE: must extend on the "non-IP-layer". Could be above L4
such as voice specific metrics, but also L2 such as (G)MPLS
2.2. Organization of this document
This document is divided in two major sections beyond the Purpose and
Scope section. The first is a definition and description of a
performance metric and its key aspects. The second defines a process
to develop these metrics that is applicable to the IETF environment.
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3. Terminology
3.1. Quality of Service
The Quality of Service (QoS) is defined similarly to the ITU "QoS
experienced/perceived by customer/user (QoSE)" E800 [E800], i.e.:
Totality of characteristics of a telecommunications service that bear
on its ability to satisfy stated and implied needs of the user of the
service.
EDITOR'S NOTE: currently searching for a QoS definition in the IETF
3.2. Application Performance Metric
EDITOR'S NOTE: to be filled in
3.3. Quality of Experience
The Quality of Experience (QoE) is defined similarly to the ITU "QoS
experienced/perceived by customer/user (QoSE)" E800 [E800], i.e.: a
statement expressing the level of quality that customers/users
believe they have experienced.
NOTE 1 - The level of QoS experienced and/or perceived by the
customer/user may be expressed by an opinion rating.
NOTE 2 - QoSE has two main man components: quantitative and
qualitative. The quantitative component can be influenced by the
complete end-to-end system effects (network infrastructure).
NOTE 3 - The qualitative component can be influenced by user
expectations, ambient conditions, psychological factors, application
context, etc.
NOTE 4 - QoSE may also be considered as QoSD received and interpreted
by a user with the pertinent qualitative factors influencing his/her
perception of the service.
4. Purpose and Scope
The purpose of this document is to define a framework and a process
for developing performance metrics for IP-based applications that
operate over reliable or datagram transport protocols, and that can
be used to characterize traffic on live networks and services. As
such, this document will not define any performance metrics.
The scope of this document includes the support of metric definition
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for any protocol developed by the IETF. However this document is not
intended to supercede existing working methods within Working Groups
that have existing chartered work in this area.
This process is not intended to govern performance metric development
in existing IETF WG that are focused on metrics development, such as
IPPM and BMWG. However, the framework and guidelines may be useful
in these activities, and MAY be applied where appropriate. A typical
example is the development of performance metrics to be exported with
the IPFIX protocol RFC 5101 [RFC5101], with specific IPFIX
information elements RFC 5102 [RFC5102], which would benefit from the
framework in this document.
The framework in this document applies to performance metrics derived
from both active and passive measurements.
5. QoS versus Application Performance Metrics versus QoE
QoS deals with the network and protocol, while QoE deals with the
notion of a user in a context of a task or a service. As a
consequence, QoE leads to the notion of Application Performance
Metrics. For example, QoS performance metrics contain the one-way
delay and the delay variation RFC 5481 [RFC5481] and the Mean Opinion
Score (MOS) P.800 [P.800] can be modelled and calculated as an
Application Performance Metric for multimedia applications. However,
the MOS for a particular user in the specific context such as a
conference call, an IPTV or an emergency call are different QoE's.
Finally, QoS and Application Performance Metrics are quantitative,
while QoE is qualitative.
EDITOR'S NOTE: not too happy about the MOS example, as it's debatable
whether MOS is QoE or Applicatoin Performance Metric? If there is a
better example...
6. Metrics Development
This section provides key definitions and qualifications of
performance metrics.
6.1. Identifying and Categorizing the Audience
Many of the aspects of metric definition and reporting, even the
selection or determination of the essential metrics, depend on who
will use the results, and for what purpose: in order to properly
maintain service quality? or to identify and quantify problems? The
question, "How will the results be used?" usually yields important
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factors to consider when developing performance metrics.
All documents defining performance metrics SHOULD identify the
primary audience and its associated requirements. The audience can
influence both the definition of metrics and the methods of
measurement.
The key areas of variation between different metric users include:
o Suitability of passive measurements of live traffic, or active
measurements using dedicated traffic
o Measurement in laboratory environment, or on a network of deployed
devices
o Suitability of passive measurements of live traffic, or active
measurements using dedicated traffic
o Measurement in laboratory environment, or on a network of deployed
devices
o Accuracy of the results
o Access to measurement points and configuration information
o Measurement topology (point-to-point, point-to-multipoint)
o Scale of the measurement system
o Measurements conducted on-demand, or continuously
o Required reporting formats
6.2. Definitions of a Metric
A metric is a measure of an observable behavior of an networking
technology, an application, or a service. Most of the time, the
metric can be directly measured. However, sometimes, the metric
definition is computed: it assumes some implicit or explicit
underlying statistical process. In such case, the metric is an
estimate of a parameter of this process, assuming that that the
statistical process closely models the behavior of the system.
A metric should serve some defined purpose. This may include the
measurement of capacity, quantifying how bad some problem is,
measurement of service level, problem diagnosis or location and other
such uses. A metric may also be an input to some other process, for
example the computation of a composite metric or a model or
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simulation of a system. Tests of the "usefulness" of a metric
include:
(i) the degree to which its absence would cause significant loss
of information on the behavior or performance of the application
or system being measured
(ii) the correlation between the performance metric, the QoS G1000
[G1000] and QoE delivered to the user (person or other
application)
(iii) the degree to which the metric is able to support the
identification and location of problems affecting service quality.
(iv) the requirement to develop policies (Service Level Agreement,
and potentially Service Level Contract) based on the metric.
For example, consider a distributed application operating over a
network connection that is subject to packet loss. A Packet Loss
Rate (PLR) metric is defined as the mean packet loss rate over some
time period. If the application performs poorly over network
connections with high packet loss rate and always performs well when
the packet loss rate is zero then the PLR metric is useful to some
degree. Some applications are sensitive to short periods of high
loss (bursty loss) and are relatively insensitive to isolated packet
loss events; for this type of application there would be very weak
correlation between PLR and application performance. A "better"
metric would consider both the packet loss rate and the distribution
of loss events. If application performance is degraded when the PLR
exceeds some rate then a useful metric may be a measure of the
duration and frequency of periods during which the PLR exceeds that
rate.
6.3. Computed Metrics
6.3.1. Composed Metrics
Some metrics may not be measured directly, but may be composed from
base metrics that have been measured. A composed metric is derived
from other metrics by applying a deterministic process or function
(e.g., a composition function). The process may use metrics that are
identical to the metric being composed, or metrics that are
dissimilar, or some combination of both types.Usually the base
metrics have a limited scope in time or space, and they can be
combined to estimate the performance of some larger entities.
Some examples of composed metrics and composed metric definitions
are:
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Spatial Composition is defined as the composition of metrics of the
same type with differing spatial domains
[I-D.ietf-ippm-framework-compagg]
[I-D.ietf-ippm-spatial-composition]. For spatially composed metrics
to be meaningful, the spatial domains should be non- overlapping and
contiguous, and the composition operation should be mathematically
appropriate for the type of metric.
Temporal Composition is defined as the composition of sets of metrics
of the same type with differing time spans
[I-D.ietf-ippm-framework-compagg]. For temporally composed metrics
to be meaningful, the time spans should be non-overlapping and
contiguous, and the composition operation should be mathematically
appropriate for the type of metric.
Temporal Aggregation is a summarization of metrics into a smaller
number of metrics that relate to the total time span covered by the
original metrics. An example would be to compute the minimum,
maximum and average values of a series of time sampled values of a
metric.
EDITOR'S NOTE: review draft-ietf-ippm-framework-compagg-08.txt and
determine is something should be added in this section
EDITOR'S NOTE: should we mention the IPFIX Mediators drafts that
explains about aggregation? http://www.ietf.org/id/
draft-ietf-ipfix-mediators-problem-statement-06.txt
http://www.ietf.org/id/draft-ietf-ipfix-mediators-framework-04.txt
6.3.2. Index (from compagg)
An Index is a metric for which the output value range has been
selected for convenience or clarity, and the behavior of which is
selected to support ease of understanding (e.g. G.107 R Factor).
The deterministic function for an index is often developed after the
index range and behavior have been determined.
EDITOR'S NOTE: the section title was "Index (from compagg)". I guess
it refers to
http://www.ietf.org/id/draft-ietf-ippm-framework-compagg-08.txt
section 3.5 "composed metrics" now. Do we want to keep a separate
sub section, or do we combine this with the previous section?
6.4. Metric Specification
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6.4.1. Outline
A metric definition MUST have a normative part that defines what the
metric is and how it is measured or computed and SHOULD have an
informative part that describes the metric and its application.
6.4.2. Normative parts of metric definition
The normative part of a metric definition MUST define at least the
following:
(i) Metric Name
Metric names MUST be unique within the set of metrics being defined
and MAY be descriptive.
(ii) Metric Description
The description MUST explain what the metric is, what is being
measured and how this relates to the performance of the system being
measured.
(iii) Collection Method
EDITOR'S NOTE: remove "measurement" in "measurement method" as this
this method can be measured, estimated or computed". Looking for a
generic term -> collection method? Do we want to change from
measurement to collection all over?
This MUST define what is being measured, estimated or computed and
the specific algorithm to be used. Terms such as "average" should be
qualified (e.g. running average or average over some interval).
Exception cases SHOULD also be defined with the appropriate handling
method. For example, there are a number of commonly used metrics
related to packet loss; these often don't define the criteria by
which a packet is determined to be lost (vs very delayed) or how
duplicate packets are handled. For example, if the average packet
loss rate during a time interval is reported, and a packet's arrival
is delayed from one interval to the next then was it "lost" during
the interval during which it should have arrived or should it be
counted as received?
Some parameters linked to the method MAY also be reported, in order
to fully interpret the performance metric. For example, the time
interval, the load, the minimum packet loss, etc...
(iv) Units of measurement
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The units of measurement MUST be clearly stated.
(v) Measurement Point(s)
If the measurement is specific to a measurement point this SHOULD be
defined. The measurement domain MAY also be defined. Specifically,
if measurement points are spread across domains, the measurement
domain (intra-, inter-) is another factor to consider.
EDITOR'S NOTE: discuss that the collection is not necessarily scoped
to a single observation point.
(vi) Measurement timing
The acceptable range of timing intervals or sampling intervals for a
measurement and the timing accuracy required for such intervals MUST
be specified. Short sampling intervals or frequent samples provide a
rich source of information that can help to assess application
performance but may lead to excessive measurement data. Long
measurement or sampling intervals reduce the amount of reported and
collected data such that it may be insufficient to understand
application performance or service quality insofar as the measured
quantity may vary significantly with time.
EDITOR'S NOTE: explain that, in case of multiple measurement points,
synchronized clocks might be required. See RFC5481
6.4.3. Informative parts of metric definition
The informative part of a metric specification is intended to support
the implementation and use of the metric. This part SHOULD provide
the following data:
(i) Implementation
The implementation description MAY be in the form of text, algorithm
or example software. The objective of this part of the metric
definition is to assist implementers to achieve a consistent result.
(ii) Verification
The metric definition SHOULD provide guidance on verification
testing. This may be in the form of test vectors, a formal
verification test method or informal advice.
(iii) Use and Applications
The Use and Applications description is intended to assist the "user"
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to understand how, when and where the metric can be applied, and what
significance the value range for the metric may have. This MAY
include a definition of the "typical" and "abnormal" range of the
metric, if this was not apparent from the nature of the metric.
For example:
(a) it is fairly intuitive that a lower packet loss rate would equate
to better performance. However the user may not know the
significance of some given packet loss rate,
(b) the speech level of a telephone signal is commonly expressed in
dBm0. If the user is presented with:
Speech level = -7 dBm0
this is not intuitively understandable, unless the user is a
telephony expert. If the metric definition explains that the typical
range is -18 to -28 dBm0, a value higher than -18 means the signal
may be too high (loud) and less than -28 means that the signal may be
too low (quiet), it is much easier to interpret the metric.
(iv) Reporting Model
The Reporting Model definition is intended to make any relationship
between the metric and the reporting model clear. There are often
implied relationships between the method of reporting metrics and the
metric itself, however these are often not made apparent to the
implementor. For example, if the metric is a short term running
average packet delay variation (e.g. PPDV as defined in RFC3550) and
this value is reported at intervals of 6-10 seconds, the resulting
measurement may have limited accuracy when packet delay variation is
non-stationary.
6.4.4. Metric Definition Template
Normative
o Metric Name
o Metric Description
o Method
o Units of measurement
o Measurement Timing
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Informative
o Implementation Guidelines
o Verification
o Use and Applications
o Reporting Model
6.4.5. Example: Burst Packet Loss Frequency
The burst packet loss frequency can be observed at different layers.
The following example is specific to RTP RFC 3550 [RFC3550].
Metric Name: BurstPacketLossFrequency
Metric Description: A burst of packet loss is defined as a longest
period starting and ending with lost packets during which no more
than Gmin consecutive packets are received. The
BurstPacketLossFrequency is defined as the number of bursts of packet
loss occurring during a specified time interval (e.g. per minute, per
hour, per day). If Gmin is set to 0 then a burst of packet loss
would comprise only consecutive lost packets, whereas a Gmin of 16
would define bursts as periods of both lost and received packets
(sparse bursts) having a loss rate of greater than 5.9%.
Method: Bursts may be detected using the Markov Model algorithm
defined in RFC3611. The BurstPacketLossFrequency is calculated by
counting the number of burst events within the defined measurement
interval. A burst that spans the boundary between two time intervals
shall be counted within the later of the two intervals.
Units of Measurement: Bursts per time interval (e.g. per second, per
hour, per day)
Measurement Timing: This metric can be used over a wide range of time
intervals. Using time intervals of longer than one hour may prevent
the detection of variations in the value of this metric due to time-
of-day changes in network load. Timing intervals should not vary in
duration by more than +/- 2%.
Implementation Guidelines: See RFC3611.
Verification Testing: See Appendix for C code to generate test
vectors.
Use and Applications: This metric is useful to detect IP network
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transients that affect the performance of applications such as Voice
over IP or IP Video. The value of Gmin may be selected to ensure
that bursts correspond to a packet loss rate that would degrade the
performance of the application of interest (e.g. 16 for VoIP).
Reporting Model: This metric needs to be associated with a defined
time interval, which could be defined by fixed intervals or by a
sliding window.
6.5. Dependencies
6.5.1. Timing accuracy
The accuracy of the timing of a measurement may affect the accuracy
of the metric. This may not materially affect a sampled value metric
however would affect an interval based metric. Some metrics, for
example the number of events per time interval, would be directly
affected; for example a 10% variation in time interval would lead
directly to a 10% variation in the measured value. Other metrics,
such as the average packet loss rate during some time interval, would
be affected to a lesser extent.
If it is necessary to correlate sampled values or intervals then it
is essential that the accuracy of sampling time and interval start/
stop times is sufficient for the application (for example +/- 2%).
6.5.2. Dependencies of metric definitions on related events or metrics
Metric definitions may explicitly or implicitly rely on factors that
may not be obvious. For example, the recognition of a packet as
being "lost" relies on having some method to know the packet was
actually lost (e.g. RTP sequence number), and some time threshold
after which a non-received packet is declared as lost. It is
important that any such dependencies are recognized and incorporated
into the metric definition.
6.5.3. Relationship between application performance and lower layer
metrics
Lower layer metrics may be used to compute or infer the performance
of higher layer applications, potentially using an application
performance model. The accuracy of this will depend on many factors
including:
(i) The completeness of the set of metrics - i.e. are there metrics
for all the input values to the application performance model?
(ii) Correlation between input variables (being measured) and
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application performance
(iii) Variability in the measured metrics and how this variability
affects application performance
6.5.4. Middlebox presence
Presence of a middlebox RFC 3303 [RFC3303], e.g., proxy, NAT,
redirect server, session border controller (SBC), and application
layer gateway (ALG) may add variability to or restrict the scope of
measurements of a metric. For example, an SBC that does not process
RTP loopback packets may block or locally terminate this traffic
rather then pass it through to its target.
6.6. Organization of Results
The IPPM Framework [RFC2330] organizes the results of metrics into
three related notions:
o singleton, an elementary instance, or "atomic" value.
o sample, a set of singletons with some common properties and some
varying properties.
o statistic, a value derived from a sample through deterministic
calculation, such as the mean.
Many metrics can use this organization for the results, with or
without the term names used by IPPM working group. Section 11 of RFC
2330 [RFC2330] should consulted for further details.
6.7. Parameters, the variables of a metric
Metrics are completely defined when all options and input variables
have been identified and considered. These variables are sometimes
left unspecified in a metric definition, and their general name
indicates that the user must set them and report them with the
results. Such variables are called "parameters" in the IPPM metric
template. The scope of the metric, the time at which it was
conducted, the settings for timers and the thresholds for counters
are all examples of parameters.
All documents defining performance metrics SHOULD identify ALL key
parameters for each metric.
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7. Performance Metric Development Process
7.1. New Proposals for Metrics
The following entry criteria will be considered for each proposal.
Proposals SHOULD be prepared as Internet Drafts, describing the
metrics and conforming to the qualifications above as much as
possible.
Proposals SHOULD be vetted by the corresponding protocol development
Working Group prior to discussion by the PM Entity. This aspect of
the process includes an assessment of the need for the metrics
proposed and assessment of the support for their development in IETF.
Proposals SHOULD include an assessment of interaction and/or overlap
with work in other Standards Development Organizations.
Proposals SHOULD specify the intended audience and users of the
metrics. The development process encourages participation by members
of the intended audience.
Proposals SHOULD survey the existing standards work in the area and
identify additional expertise that might be consulted, or possible
overlap with other standards development orgs.
Proposals SHOULD identify any security and IANA requirements.
Security issues could potentially involve revealing of user
identifying data or the potential misuse of active test tools. IANA
considerations may involve the need for a metrics registry.
7.2. Reviewing Metrics
Each metric SHOULD be assessed according to the following list of
qualifications:
o Unambiguously defined?
o Units of Measure Specified?
o Measurement Interval Specified?
o Measurement Errors Identified?
o Repeatable?
o Implementable?
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o Assumptions concerning underlying process?
o Use cases?
o Correlation with application performance/ user experience?
7.3. Proposal Approval
New work item proposals SHALL be approved using the existing IETF
process.
The process depends on the form that the PM Entity ultimately takes,
Directorate or working group.
In all cases, the proposal will need to achieve consensus, in the
corresponding protocol development working group (or alternatively,
an "Area" working group with broad charter), that there is interest
and a need for the work.
IF the PM Entity is a Directorate,
THEN Approval SHOULD include the following steps
o consultation with the PM Directorate, using this framework
document
o consultation with Area Director(s)
o and possibly IESG approval of a new or revised charter for the
working group
IF the PM Entity is a Working Group, and the protocol development
working group decides to take up the work under its charter,
THEN the approval is the same as the PM Directorate steps above, with
the possible additional assignment of a PM Advisor for the work item.
IF the PM Entity is a Working Group, and the protocol development
working group decides it does not have sufficient expertise to
take-up the work, or the proposal falls outside the current charter,
THEN
Approval SHOULD include the following steps
o identification of protocol expertise to support metric development
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o consensus in the PM working group that there is interest and a
need for the work, and that a document conforming to this
framework can be successfully developed
o consultation with Area Director(s)
o IESG approval of a revised charter for the PM working group
7.4. PM Entity Interaction with other WGs
The PM Entity SHALL work in partnership with the related protocol
development WG when considering an Internet Draft that specifies
performance metrics for a protocol. A sufficient number of
individuals with expertise must be willing to consult on the draft.
If the related WG has concluded, comments on the proposal should
still be sought from key RFC authors and former chairs, or from the
WG mailing list if it was not closed.
Existing mailing lists SHOULD be used however a dedicated mailing
list MAY be initiated if necessary to facilitate work on a draft.
In some cases, it will be appropriate to have the IETF session
discussion during the related protocol WG session, to maximize
visibility of the effort to that WG and expand the review.
7.5. Standards Track Performance Metrics
The PM Entity will manage the progression of PM RFCs along the
Standards Track. See [I-D.bradner-metricstest]. This may include
the preparation of test plans to examine different implementations of
the metrics to ensure that the metric definitions are clear and
unambiguous (depending on the final form of the draft above).
8. IANA Considerations
This document makes no request of IANA.
Note to RFC Editor: this section may be removed on publication as an
RFC.
9. Security Considerations
In general, the existence of framework for performance metric
development does not constitute a security issue for the Internet.
Metric definitions may introduce security issues and this framework
recommends that those defining metrics should identify any such risk
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factors.
The security considerations that apply to any active measurement of
live networks are relevant here as well. See [RFC4656].
EDITOR'S NOTE: do we want to mention something about specific to
passive? For example, anonymization.
10. Acknowledgements
The authors would like to thank Al Morton, Dan Romascanu, Daryl Malas
and Loki Jorgenson for their comments and contributions.
11. References
11.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M.
Zekauskas, "A One-way Active Measurement Protocol
(OWAMP)", RFC 4656, September 2006.
11.2. Informative References
[E800] "ITU-T Recommendation E.800. SERIES E: OVERALL NETWORK
OPERATION, TELEPHONE SERVICE, SERVICE OPERATION AND HUMAN
FACTORS".
[G1000] "ITU-T Recommendation G.1000. Communications Quality of
Service: A framework and definitions".
[I-D.bradner-metricstest]
Bradner, S. and V. Paxson, "Advancement of metrics
specifications on the IETF Standards Track",
draft-bradner-metricstest-03 (work in progress),
August 2007.
[I-D.ietf-ippm-framework-compagg]
Morton, A., "Framework for Metric Composition",
draft-ietf-ippm-framework-compagg-08 (work in progress),
June 2009.
[I-D.ietf-ippm-spatial-composition]
Morton, A. and E. Stephan, "Spatial Composition of
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Metrics", draft-ietf-ippm-spatial-composition-10 (work in
progress), October 2009.
[P.800] "ITU-T Recommendation P.800. : Methods for subjective
determination of transmission quality".
[RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis,
"Framework for IP Performance Metrics", RFC 2330,
May 1998.
[RFC3303] Srisuresh, P., Kuthan, J., Rosenberg, J., Molitor, A., and
A. Rayhan, "Middlebox communication architecture and
framework", RFC 3303, August 2002.
[RFC3550] Schulzrinne, H., Casner, S., Frederick, R., and V.
Jacobson, "RTP: A Transport Protocol for Real-Time
Applications", STD 64, RFC 3550, July 2003.
[RFC4710] Siddiqui, A., Romascanu, D., and E. Golovinsky, "Real-time
Application Quality-of-Service Monitoring (RAQMON)
Framework", RFC 4710, October 2006.
[RFC5101] Claise, B., "Specification of the IP Flow Information
Export (IPFIX) Protocol for the Exchange of IP Traffic
Flow Information", RFC 5101, January 2008.
[RFC5102] Quittek, J., Bryant, S., Claise, B., Aitken, P., and J.
Meyer, "Information Model for IP Flow Information Export",
RFC 5102, January 2008.
[RFC5481] Morton, A. and B. Claise, "Packet Delay Variation
Applicability Statement", RFC 5481, March 2009.
Authors' Addresses
Alan Clark
Telchemy Incorporated
2905 Premiere Parkway, Suite 280
Duluth, Georgia 30097
USA
Phone:
Fax:
Email: alan.d.clark@telchemy.com
URI:
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Benoit Claise
Cisco Systems, Inc.
De Kleetlaan 6a b1
Diegem 1831
Belgium
Phone: +32 2 704 5622
Fax:
Email: bclaise@cisco.com
URI:
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