draft-ietf-ippm-loss-episode-metrics-04.txt   rfc6534.txt 
Network Working Group N. Duffield Internet Engineering Task Force (IETF) N. Duffield
Internet-Draft AT&T Labs-Research Request for Comments: 6534 AT&T Labs-Research
Intended status: Standards Track A. Morton Category: Standards Track A. Morton
Expires: July 20, 2012 AT&T Labs ISSN: 2070-1721 AT&T Labs
J. Sommers J. Sommers
Colgate University Colgate University
January 17, 2012 May 2012
Loss Episode Metrics for IPPM Loss Episode Metrics for IP Performance Metrics (IPPM)
draft-ietf-ippm-loss-episode-metrics-04
Abstract Abstract
The IETF has developed a one way packet loss metric that measures the The IETF has developed a one-way packet loss metric that measures the
loss rate on a Poisson probe stream between two hosts. However, the loss rate on a Poisson and Periodic probe streams between two hosts.
impact of packet loss on applications is in general sensitive not However, the impact of packet loss on applications is, in general,
just to the average loss rate, but also to the way in which packet sensitive not just to the average loss rate but also to the way in
losses are distributed in loss episodes (i.e., maximal sets of which packet losses are distributed in loss episodes (i.e., maximal
consecutively lost probe packets). This document defines one-way sets of consecutively lost probe packets). This document defines
packet loss episode metrics, specifically the frequency and average one-way packet loss episode metrics, specifically, the frequency and
duration of loss episodes, and a probing methodology under which the average duration of loss episodes and a probing methodology under
loss episode metrics are to be measured. which the loss episode metrics are to be measured.
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]
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 July 20, 2012. 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/rfc6534.
Copyright Notice Copyright Notice
Copyright (c) 2012 IETF Trust and the persons identified as the Copyright (c) 2012 IETF Trust and the persons identified as the
document authors. All rights reserved. document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal This document is subject to BCP 78 and the IETF Trust's Legal
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to this document. Code Components extracted from this document must to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of include Simplified BSD License text as described in Section 4.e of
skipping to change at page 3, line 7 skipping to change at page 2, line 22
modifications of such material outside the IETF Standards Process. modifications of such material outside the IETF Standards Process.
Without obtaining an adequate license from the person(s) controlling Without obtaining an adequate license from the person(s) controlling
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outside the IETF Standards Process, and derivative works of it may outside the IETF Standards Process, and derivative works of it may
not be created outside the IETF Standards Process, except to format not be created outside the IETF Standards Process, except to format
it for publication as an RFC or to translate it into languages other it for publication as an RFC or to translate it into languages other
than English. than English.
Table of Contents Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 5 1. Introduction ....................................................4
1.1. Background and Motivation . . . . . . . . . . . . . . . . 5 1.1. Background and Motivation ..................................4
1.2. Loss Episode Metrics and Bi-Packet Probes . . . . . . . . 6 1.1.1. Requirements Language ...............................5
1.3. Outline and Contents . . . . . . . . . . . . . . . . . . . 7 1.2. Loss Episode Metrics and Bi-Packet Probes ..................5
2. Singleton Definition for Type-P-One-way Bi-Packet Loss . . . . 8 1.3. Outline and Contents .......................................6
2.1. Metric Name . . . . . . . . . . . . . . . . . . . . . . . 8 2. Singleton Definition for Type-P-One-way Bi-Packet Loss ..........7
2.2. Metric Parameters . . . . . . . . . . . . . . . . . . . . 8 2.1. Metric Name ................................................7
2.3. Metric Units . . . . . . . . . . . . . . . . . . . . . . . 8 2.2. Metric Parameters ..........................................7
2.4. Metric Definition . . . . . . . . . . . . . . . . . . . . 8 2.3. Metric Units ...............................................7
2.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . 9 2.4. Metric Definition ..........................................7
2.6. Methodologies . . . . . . . . . . . . . . . . . . . . . . 9 2.5. Discussion .................................................8
2.7. Errors and Uncertainties . . . . . . . . . . . . . . . . . 9 2.6. Methodologies ..............................................8
2.8. Reporting the Metric . . . . . . . . . . . . . . . . . . . 9 2.7. Errors and Uncertainties ...................................8
3. General Definition of samples for 2.8. Reporting the Metric .......................................8
Type-P-One-way-Bi-Packet-Loss . . . . . . . . . . . . . . . . 9 3. General Definition of Samples for
3.1. Metric Name . . . . . . . . . . . . . . . . . . . . . . . 10 Type-P-One-way-Bi-Packet-Loss ...................................8
3.2. Metric Parameters . . . . . . . . . . . . . . . . . . . . 10 3.1. Metric Name ................................................9
3.3. Metric Units . . . . . . . . . . . . . . . . . . . . . . . 10 3.2. Metric Parameters ..........................................9
3.4. Metric Definition . . . . . . . . . . . . . . . . . . . . 10 3.3. Metric Units ...............................................9
3.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . 10 3.4. Metric Definition ..........................................9
3.6. Methodologies . . . . . . . . . . . . . . . . . . . . . . 10 3.5. Discussion .................................................9
3.7. Errors and Uncertainties . . . . . . . . . . . . . . . . . 11 3.6. Methodologies .............................................10
3.8. Reporting the Metric . . . . . . . . . . . . . . . . . . . 11 3.7. Errors and Uncertainties ..................................10
4. An active probing methodology for Bi-Packet Loss . . . . . . . 11 3.8. Reporting the Metric ......................................10
4.1. Metric Name . . . . . . . . . . . . . . . . . . . . . . . 11 4. An Active Probing Methodology for Bi-Packet Loss ...............10
4.2. Metric Parameters . . . . . . . . . . . . . . . . . . . . 11 4.1. Metric Name ...............................................10
4.3. Metric Units . . . . . . . . . . . . . . . . . . . . . . . 12 4.2. Metric Parameters .........................................10
4.4. Metric Definition . . . . . . . . . . . . . . . . . . . . 12 4.3. Metric Units ..............................................11
4.5. Discussion . . . . . . . . . . . . . . . . . . . . . . . . 12 4.4. Metric Definition .........................................11
4.6. Methodologies . . . . . . . . . . . . . . . . . . . . . . 12 4.5. Discussion ................................................11
4.7. Errors and Uncertainties . . . . . . . . . . . . . . . . . 13 4.6. Methodologies .............................................11
4.8. Reporting the Metric . . . . . . . . . . . . . . . . . . . 13 4.7. Errors and Uncertainties ..................................12
5. Loss Episode Proto-Metrics . . . . . . . . . . . . . . . . . . 13 4.8. Reporting the Metric ......................................12
5.1. Loss-Pair-Counts . . . . . . . . . . . . . . . . . . . . . 13 5. Loss Episode Proto-Metrics .....................................12
5.2. Bi-Packet-Loss-Ratio . . . . . . . . . . . . . . . . . . . 14 5.1. Loss-Pair-Counts ..........................................13
5.3. Bi-Packet-Loss-Episode-Duration-Number . . . . . . . . . . 14 5.2. Bi-Packet-Loss-Ratio ......................................13
5.4. Bi-Packet-Loss-Episode-Frequency-Number . . . . . . . . . 14 5.3. Bi-Packet-Loss-Episode-Duration-Number ....................13
6. Loss Episode Metrics derived from Bi-Packet Loss Probing . . . 14 5.4. Bi-Packet-Loss-Episode-Frequency-Number ...................13
6.1. Geometric Stream: Loss Ratio . . . . . . . . . . . . . . . 15 6. Loss Episode Metrics Derived from Bi-Packet Loss Probing .......14
6.1.1. Metric Name . . . . . . . . . . . . . . . . . . . . . 15 6.1. Geometric Stream: Loss Ratio ..............................14
6.1.2. Metric Parameters . . . . . . . . . . . . . . . . . . 15 6.1.1. Metric Name ........................................14
6.1.3. Metric Units . . . . . . . . . . . . . . . . . . . . . 16 6.1.2. Metric Parameters ..................................14
6.1.4. Metric Definition . . . . . . . . . . . . . . . . . . 16 6.1.3. Metric Units .......................................15
6.1.5. Discussion . . . . . . . . . . . . . . . . . . . . . . 16 6.1.4. Metric Definition ..................................15
6.1.6. Methodologies . . . . . . . . . . . . . . . . . . . . 16 6.1.5. Discussion .........................................15
6.1.7. Errors and Uncertainties . . . . . . . . . . . . . . . 16 6.1.6. Methodologies ......................................15
6.1.8. Reporting the Metric . . . . . . . . . . . . . . . . . 16 6.1.7. Errors and Uncertainties ...........................15
6.2. Geometric Stream: Loss Episode Duration . . . . . . . . . 16 6.1.8. Reporting the Metric ...............................15
6.2.1. Metric Name . . . . . . . . . . . . . . . . . . . . . 16 6.2. Geometric Stream: Loss Episode Duration ...................16
6.2.2. Metric Parameters . . . . . . . . . . . . . . . . . . 16 6.2.1. Metric Name ........................................16
6.2.3. Metric Units . . . . . . . . . . . . . . . . . . . . . 17 6.2.2. Metric Parameters ..................................16
6.2.4. Metric Definition . . . . . . . . . . . . . . . . . . 17 6.2.3. Metric Units .......................................16
6.2.5. Discussion . . . . . . . . . . . . . . . . . . . . . . 17 6.2.4. Metric Definition ..................................16
6.2.6. Methodologies . . . . . . . . . . . . . . . . . . . . 17 6.2.5. Discussion .........................................16
6.2.7. Errors and Uncertainties . . . . . . . . . . . . . . . 17 6.2.6. Methodologies ......................................16
6.2.8. Reporting the Metric . . . . . . . . . . . . . . . . . 18 6.2.7. Errors and Uncertainties ...........................17
6.3. Geometric Stream: Loss Episode Frequency . . . . . . . . . 18 6.2.8. Reporting the Metric ...............................17
6.3.1. Metric Name . . . . . . . . . . . . . . . . . . . . . 18 6.3. Geometric Stream: Loss Episode Frequency ..................17
6.3.2. Metric Parameters . . . . . . . . . . . . . . . . . . 18 6.3.1. Metric Name ........................................17
6.3.3. Metric Units . . . . . . . . . . . . . . . . . . . . . 18 6.3.2. Metric Parameters ..................................17
6.3.4. Metric Definition . . . . . . . . . . . . . . . . . . 18 6.3.3. Metric Units .......................................17
6.3.5. Discussion . . . . . . . . . . . . . . . . . . . . . . 19 6.3.4. Metric Definition ..................................18
6.3.6. Methodologies . . . . . . . . . . . . . . . . . . . . 19 6.3.5. Discussion .........................................18
6.3.7. Errors and Uncertainties . . . . . . . . . . . . . . . 19 6.3.6. Methodologies ......................................18
6.3.8. Reporting the Metric . . . . . . . . . . . . . . . . . 19 6.3.7. Errors and Uncertainties ...........................18
7. Applicability of Loss Episode Metrics . . . . . . . . . . . . 19 6.3.8. Reporting the Metric ...............................18
7.1. Relation to Gilbert Model . . . . . . . . . . . . . . . . 19 7. Applicability of Loss Episode Metrics ..........................18
8. IPR Considerations . . . . . . . . . . . . . . . . . . . . . . 20 7.1. Relation to Gilbert Model .................................18
9. Security Considerations . . . . . . . . . . . . . . . . . . . 20 8. Security Considerations ........................................19
10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 21 9. References .....................................................20
11. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 21 9.1. Normative References ......................................20
12. References . . . . . . . . . . . . . . . . . . . . . . . . . . 21 9.2. Informative References ....................................20
12.1. Normative References . . . . . . . . . . . . . . . . . . . 21
12.2. Informative References . . . . . . . . . . . . . . . . . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 22
1. Introduction 1. Introduction
1.1. Background and Motivation 1.1. Background and Motivation
Packet loss in the Internet is a complex phenomenon due to the bursty Packet loss in the Internet is a complex phenomenon due to the bursty
nature of traffic and congestion processes, influenced by both end- nature of traffic and congestion processes, influenced by both end-
users and applications, and the operation of transport protocols such users and applications and the operation of transport protocols such
as TCP. For these reasons, the simplest model of packet loss--the as TCP. For these reasons, the simplest model of packet loss -- the
single parameter Bernoulli (independent) loss model--does not single parameter Bernoulli (independent) loss model -- does not
represent the complexity of packet loss over periods of time. represent the complexity of packet loss over periods of time.
Correspondingly, a single loss metric--the average packet loss ratio Correspondingly, a single loss metric -- the average packet loss
over some period of time--arising, e.g., from a stream of Poisson ratio over some period of time -- arising, e.g., from a stream of
probes as in [RFC2680] is not sufficient to determine the effect of Poisson probes as in [RFC2680] is not sufficient to determine the
packet loss on traffic in general. effect of packet loss on traffic in general.
Moving beyond single parameter loss models, Markovian and Markov- Moving beyond single parameter loss models, Markovian and Markov-
modulated loss models involving transitions between a good and bad modulated loss models involving transitions between a good and bad
state, each with an associated loss rate, have been proposed by state, each with an associated loss rate, have been proposed by
Gilbert [Gilbert] and more generally by Elliot [Elliot]. In Gilbert [Gilbert] and more generally by Elliot [Elliot]. In
principle, Markovian models can be formulated over state spaces principle, Markovian models can be formulated over state spaces
involving patterns of loss of any desired number of packets. However involving patterns of loss of any desired number of packets.
further increase in the size of the state space makes such models However, further increase in the size of the state space makes such
cumbersome both for parameter estimation (accuracy decreases) and models cumbersome both for parameter estimation (accuracy decreases)
prediction in practice (due to computational complexity and and prediction in practice (due to computational complexity and
sensitivity to parameter inaccuracy). In general, the relevance and sensitivity to parameter inaccuracy). In general, the relevance and
importance of particular models can change in time, e.g. in response importance of particular models can change in time, e.g., in response
to the advent of new applications and services. For this reason we to the advent of new applications and services. For this reason, we
are drawn to empirical metrics that do not depend on a particular are drawn to empirical metrics that do not depend on a particular
model for their interpretation. model for their interpretation.
An empirical measure of packet loss complexity, the index of An empirical measure of packet loss complexity, the index of
dispersion of counts (IDC), comprise, for each t >0, the ratio v(t) / dispersion of counts (IDC), comprise, for each t >0, the ratio v(t) /
a(t) of the variance v(t) and average a(t) of the number of losses a(t) of the variance v(t) and average a(t) of the number of losses
over successive measurement windows of a duration t. However, a full over successive measurement windows of a duration t. However, a full
characterization of packet loss over time requires specification of characterization of packet loss over time requires specification of
the IDC for each window size t>0. the IDC for each window size t>0.
In the standards arena, loss pattern sample metrics are defined in In the standards arena, loss pattern sample metrics are defined in
[RFC3357]. Following the Gilbert-Elliot model, burst metrics [RFC3357]. Following the Gilbert-Elliot model, burst metrics
specific for VoIP that characterize complete episodes of lost, specific for Voice over IP (VoIP) that characterize complete episodes
transmitted and discarded packets are defined in [RFC3611] of lost, transmitted, and discarded packets are defined in [RFC3611].
All these considerations motivate formulating empirical metrics of The above considerations motivate the formulation of empirical
one-way packet loss that provide the simplest generalization of the metrics of one-way packet loss that provide the simplest
successful [RFC2680] that can capture deviations from independent generalization of [RFC2680] (which is widely adopted but only defines
packet loss in a robust model-independent manner, and, to define a single loss-to-total ratio metric). The metrics defined here
efficient measurement methodologies for these metrics. capture deviations from independent packet loss in a robust model-
independent manner. The document also defines efficient measurement
methodologies for these metrics.
1.1.1. 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].
1.2. Loss Episode Metrics and Bi-Packet Probes 1.2. Loss Episode Metrics and Bi-Packet Probes
The losses experienced by the packet stream can be viewed as The losses experienced by the packet stream can be viewed as
occurring in loss episodes, i.e., maximal set of consecutively lost occurring in loss episodes, i.e., a maximal set of consecutively lost
packets. This memo describes one-way loss episode metrics: their packets. This memo describes one-way loss episode metrics: their
frequency and average duration. Although the average loss ratio can frequency and average duration. Although the average loss ratio can
be expressed in terms of these quantities, they go further in be expressed in terms of these quantities, they go further in
characterizing the statistics of the patterns of packet loss within characterizing the statistics of the patterns of packet loss within
the stream of probes. This is useful information in understanding the stream of probes. This is useful information in understanding
the effect of packet losses on application performance, since the effect of packet losses on application performance, since
different applications can have different sensitivities to patterns different applications can have different sensitivities to patterns
of loss, being sensitive not only to the long term average loss rate, of loss, being sensitive not only to the long-term average loss rate,
but how losses are distributed in time. As an example: MPEG video but how losses are distributed in time. As an example, MPEG video
traffic may be sensitive to loss involving the I-frame in a group of traffic may be sensitive to loss involving the I-frame in a group of
pictures, but further losses within an episode of sufficiently short pictures, but further losses within an episode of sufficiently short
duration have no further impact; the damage is already done. duration have no further impact; the damage is already done.
The loss episode metrics presented here have the following useful The loss episode metrics presented here have the following useful
properties: properties:
1. the metrics are empirical and do not depend on an underlying 1. the metrics are empirical and do not depend on an underlying
model; e.g., the loss process is not assumed to be Markovian. On model; e.g., the loss process is not assumed to be Markovian. On
the other hand, it turns out that the metrics of this memo can be the other hand, it turns out that the metrics of this memo can be
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Section 7. Section 7.
2. the metric units can be directly compared with applications or 2. the metric units can be directly compared with applications or
user requirements or tolerance for network loss performance, in user requirements or tolerance for network loss performance, in
the frequency and duration of loss episodes, as well as the usual the frequency and duration of loss episodes, as well as the usual
packet loss ratio, which can be recovered from the loss episode packet loss ratio, which can be recovered from the loss episode
metrics upon dividing the average loss episode duration by the metrics upon dividing the average loss episode duration by the
loss episode frequency. loss episode frequency.
3. the metrics provide the smallest possible increment in complexity 3. the metrics provide the smallest possible increment in complexity
beyond, but in the spirit of, the IPPM average packet loss ratio beyond, but in the spirit of, the IP Performance Metrics (IPPM)
metrics [RFC2680] i.e., moving from a single metric (average average packet loss ratio metrics [RFC2680], i.e., moving from a
packet loss ratio) to a pair of metrics (loss episode frequency single metric (average packet loss ratio) to a pair of metrics
and average loss episode duration). (loss episode frequency and average loss episode duration).
The document also describes a probing methodology under which loss The document also describes a probing methodology under which loss
episode metrics are to be measured. The methodology comprises episode metrics are to be measured. The methodology comprises
sending probe packets in pairs, where packets within each probe pair sending probe packets in pairs, where packets within each probe pair
have a fixed separation, and the time between pairs takes the form of have a fixed separation, and the time between pairs takes the form of
a geometric distributed number multiplied by the same separation. a geometric distributed number multiplied by the same separation.
This can be regarded a generalization of Poisson probing where the This can be regarded a generalization of Poisson probing where the
probes are pairs rather than single packets as in [RFC2680], and also probes are pairs rather than single packets as in [RFC2680], and also
of geometric probing described in [RFC2330]. However, it should be of geometric probing described in [RFC2330]. However, it should be
distinguished from back to back packet pairs whose change in distinguished from back-to-back packet pairs whose change in
separation on traversing a link is used to probe bandwidth. In this separation on traversing a link is used to probe bandwidth. In this
document, the separation between the packets in a pair is the document, the separation between the packets in a pair is the
temporal resolution at which different loss episodes are to be temporal resolution at which different loss episodes are to be
distinguished. The methodology does not measure episodes of loss of distinguished. The methodology does not measure episodes of loss of
consecutive background packets on the measured path. One key feature consecutive background packets on the measured path. One key feature
of this methodology is its efficiency: it estimates the average of this methodology is its efficiency: it estimates the average
length of loss episodes without directly measuring the complete length of loss episodes without directly measuring the complete
episodes themselves. Instead, this information is encoded in the episodes themselves. Instead, this information is encoded in the
observed relative frequencies of the 4 possible outcomes arising from observed relative frequencies of the four possible outcomes arising
the loss or successful transmission of each of the two packets of the from the loss or successful transmission of each of the two packets
probe pairs. This is distinct from the approach of [RFC3611] that of the probe pairs. This is distinct from the approach of [RFC3611],
reports on directly measured episodes. which reports on directly measured episodes.
The metrics defined in this memo are "derived metrics", according to The metrics defined in this memo are "derived metrics", according to
Section 6.1 of [RFC2330] the IPPM framework. They are based on the Section 6.1 of [RFC2330] (the IPPM framework). They are based on the
singleton loss metric defined in Section 2 of [RFC2680] . singleton loss metric defined in Section 2 of [RFC2680] .
1.3. Outline and Contents 1.3. Outline and Contents
o Section 2 defines the fundamental singleton metric for the o Section 2 defines the fundamental singleton metric for the
possible outcomes of a probe pair: Type-P-One-way-Bi-Packet-Loss. possible outcomes of a probe pair: Type-P-One-way-Bi-Packet-Loss.
o Section 3 defines sample sets of this metric derived from a o Section 3 defines sample sets of this metric derived from a
general probe stream: Type-P-One-way-Bi-Packet-Loss-Stream. general probe stream: Type-P-One-way-Bi-Packet-Loss-Stream.
o Section 4 defines the prime example of the Bi-Packet-Loss-Stream o Section 4 defines the prime example of the Bi-Packet-Loss-Stream
metrics, specifically Type-P-One-way-Bi-Packet-Loss-Geometric- metrics, specifically Type-P-One-way-Bi-Packet-Loss-Geometric-
Stream arising from the geometric stream of packet-pair probes Stream arising from the geometric stream of packet-pair probes
that was described informally in Section 1. that was described informally in Section 1.
o Section 5 defines Loss episode proto-metrics that summarize the o Section 5 defines loss episode proto-metrics that summarize the
outcomes from a stream metrics as an intermediate step to forming outcomes from a stream metrics as an intermediate step to forming
the loss episode metrics; they need not be reported in general. the loss episode metrics; they need not be reported in general.
o Section 6 defines the final loss episode metrics that are the o Section 6 defines the final loss episode metrics that are the
focus of this memo, the new metrics focus of this memo, the new metrics:
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode- * Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-
Duration, the average duration, in seconds, of a loss episode Duration, the average duration, in seconds, of a loss episode.
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode- * Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-
Frequency, the average frequency, per second, at which loss Frequency, the average frequency, per second, at which loss
episodes start. episodes start.
* Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio, which is * Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio, which is
the average packet loss ratio metric arising from the geometric the average packet loss ratio metric arising from the geometric
stream probing methodology stream probing methodology
o Section 7 details applications and relations to existing loss o Section 7 details applications and relations to existing loss
skipping to change at page 8, line 25 skipping to change at page 7, line 33
o Src, the IP address of a source host o Src, the IP address of a source host
o Dst, the IP address of a destination host o Dst, the IP address of a destination host
o T1, a sending time of the first packet o T1, a sending time of the first packet
o T2, a sending time of the second packet, with T2>T1 o T2, a sending time of the second packet, with T2>T1
o F, a selection function defining unambiguously the two packets o F, a selection function defining unambiguously the two packets
from the stream selected for the metric. from the stream selected for the metric
o P, the specification of the packet type, over and above the source o P, the specification of the packet type, over and above the source
and destination addresses and destination addresses
2.3. Metric Units 2.3. Metric Units
A Loss Pair is pair (l1, l2) where each of l1 and l2 is a binary A Loss Pair is pair (l1, l2) where each of l1 and l2 is a binary
value 0 or 1, where 0 signifies successful transmission of a packet value 0 or 1, where 0 signifies successful transmission of a packet
and 1 signifies loss. and 1 signifies loss.
The metric unit of Type-P-One-way-Bi-Packet-Loss is a Loss Pair. The metric unit of Type-P-One-way-Bi-Packet-Loss is a Loss Pair.
2.4. Metric Definition 2.4. Metric Definition
1. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 1. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1,
T2, F, P) is (1,1)" means that Src sent the first bit of a Type-P T2, F, P) is (1,1)" means that Src sent the first bit of a Type-P
packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P
packet to Dst at wire-time T2>T1, and that neither packet was packet to Dst at wire-time T2>T1 and that neither packet was
received at Dst. received at Dst.
2. The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 2. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1,
T2, F, P) is (1,0)" means that Src sent the first bit of a Type-P T2, F, P) is (1,0)" means that Src sent the first bit of a Type-P
packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P
packet to Dst at wire-time T2>T1, and that the first packet was packet to Dst at wire-time T2>T1 and that the first packet was
not received at Dst, and the second packet was received at Dst not received at Dst, and the second packet was received at Dst
3. The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 3. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1,
T2, F, P) is (0,1)" means that Src sent the first bit of a Type-P T2, F, P) is (0,1)" means that Src sent the first bit of a Type-P
packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P
packet to Dst at wire-time T2>T1, and that the first packet was packet to Dst at wire-time T2>T1 and that the first packet was
received at Dst, and the second packet was not received at Dst received at Dst, and the second packet was not received at Dst
4. The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1, 4. "The Type-P-One-way-Bi-Packet-Loss with parameters (Src, Dst, T1,
T2, F, P) is (0,0)" means that Src sent the first bit of a Type-P T2, F, P) is (0,0)" means that Src sent the first bit of a Type-P
packet to Dst at wire-time T1 and the first bit of a Type-P packet to Dst at wire-time T1 and the first bit of a Type-P
packet to Dst at wire-time T2>T1, and that both packets were packet to Dst at wire-time T2>T1 and that both packets were
received at Dst. received at Dst.
2.5. Discussion 2.5. Discussion
The purpose of the selection function is to specify exactly which The purpose of the selection function is to specify exactly which
packets are to be used for measurement. The notion is taken from packets are to be used for measurement. The notion is taken from
Section 2.5 of [RFC3393], where examples are discussed. Section 2.5 of [RFC3393], where examples are discussed.
2.6. Methodologies 2.6. Methodologies
skipping to change at page 9, line 40 skipping to change at page 8, line 46
2.7. Errors and Uncertainties 2.7. Errors and Uncertainties
Sources of error for the Type-P-One-way-Packet-Loss metric in Section Sources of error for the Type-P-One-way-Packet-Loss metric in Section
2.7 of [RFC2680] apply to each packet of the pair for the Type-P-One- 2.7 of [RFC2680] apply to each packet of the pair for the Type-P-One-
way-Bi-Packet-Loss metric. way-Bi-Packet-Loss metric.
2.8. Reporting the Metric 2.8. Reporting the Metric
Refer to Section 2.8 of [RFC2680]. Refer to Section 2.8 of [RFC2680].
3. General Definition of samples for Type-P-One-way-Bi-Packet-Loss 3. General Definition of Samples for Type-P-One-way-Bi-Packet-Loss
Given the singleton metric for Type-P-One-way-Bi-Packet-Loss, we now Given the singleton metric for Type-P-One-way-Bi-Packet-Loss, we now
define examples of samples of singletons. The basic idea is as define examples of samples of singletons. The basic idea is as
follows. We first specify a set of times T1 < T2 <...<Tn, each of follows. We first specify a set of times T1 < T2 <...<Tn, each of
which acts as the first time of a packet pair for a single Type-P- which acts as the first time of a packet pair for a single Type-P-
One-way-Bi-Packet-Loss measurement. This results is a set of n One-way-Bi-Packet-Loss measurement. This results is a set of n
metric values of Type-P-One-way-Bi-Packet-Loss. metric values of Type-P-One-way-Bi-Packet-Loss.
3.1. Metric Name 3.1. Metric Name
skipping to change at page 10, line 20 skipping to change at page 9, line 23
o Src, the IP address of a source host o Src, the IP address of a source host
o Dst, the IP address of a destination host o Dst, the IP address of a destination host
o (T11,T12), (T21,T22)....,(Tn1,Tn2) a set of n times of sending o (T11,T12), (T21,T22)....,(Tn1,Tn2) a set of n times of sending
times for packet pairs, with T11 < T12 <= T21 < T22 <=...<= Tn1 < times for packet pairs, with T11 < T12 <= T21 < T22 <=...<= Tn1 <
Tn2 Tn2
o F, a selection function defining unambiguously the two packets o F, a selection function defining unambiguously the two packets
from the stream selected for the metric. from the stream selected for the metric
o P, the specification of the packet type, over and above the source o P, the specification of the packet type, over and above the source
and destination address and destination address
3.3. Metric Units 3.3. Metric Units
A set L1,L2,...,Ln of loss pairs A set L1,L2,...,Ln of Loss Pairs
3.4. Metric Definition 3.4. Metric Definition
Each loss pair Li for i-1,....n is the Type-P-One-way-Bi-Packet-Loss Each Loss Pair Li for i = 1,....n is the Type-P-One-way-Bi-Packet-
with parameters (Src, Dst, Ti1, Ti2, Fi, P) where Fi is the Loss with parameters (Src, Dst, Ti1, Ti2, Fi, P) where Fi is the
restriction of the selection function F to the packet pair at time restriction of the selection function F to the packet pair at time
Ti1, Ti2. Ti1, Ti2.
3.5. Discussion 3.5. Discussion
The metric definition of Type-P-One-way-Bi-Packet-Loss-Stream is The metric definition of Type-P-One-way-Bi-Packet-Loss-Stream is
sufficiently general to describe the case where packets are sampled sufficiently general to describe the case where packets are sampled
from a pre-existing stream. This is useful in the case that there is from a preexisting stream. This is useful in the case in which there
a general purpose measurement stream setup between two hosts, and we is a general purpose measurement stream set up between two hosts, and
wish to select a substream from it for the purposes of loss episode we wish to select a substream from it for the purposes of loss
measurement. Packet pairs selected as bi-packet loss probes need not episode measurement. Packet pairs selected as bi-packet loss probes
be consecutive within such a stream. In the next section we need not be consecutive within such a stream. In the next section,
specialize this somewhat to more concretely describe a purpose built we specialize this somewhat to more concretely describe a purpose
packet stream for loss episode measurement. built packet stream for loss episode measurement.
3.6. Methodologies 3.6. Methodologies
The methodologies related to the Type-P-One-way-Packet-Loss metric in The methodologies related to the Type-P-One-way-Packet-Loss metric in
Section 2.6 of [RFC2680] are similar for the Type-P-One-way-Bi- Section 2.6 of [RFC2680] are similar for the Type-P-One-way-Bi-
Packet-Loss-Stream metric described above. In particular, the Packet-Loss-Stream metric described above. In particular, the
methodologies described in RFC 2680 apply to both packets of each methodologies described in RFC 2680 apply to both packets of each
pair. pair.
3.7. Errors and Uncertainties 3.7. Errors and Uncertainties
Sources of error for the Type-P-One-way-Packet-Loss metric in Section Sources of error for the Type-P-One-way-Packet-Loss metric in Section
2.7 of [RFC2680] apply to each packet of each pair for the Type-P- 2.7 of [RFC2680] apply to each packet of each pair for the Type-P-
One-way-Bi-Packet-Loss-Stream metric. One-way-Bi-Packet-Loss-Stream metric.
3.8. Reporting the Metric 3.8. Reporting the Metric
Refer to Section 2.8 of [RFC2680]. Refer to Section 2.8 of [RFC2680].
4. An active probing methodology for Bi-Packet Loss 4. An Active Probing Methodology for Bi-Packet Loss
This section specializes the preceding section for an active probing This section specializes the preceding section for an active probing
methodology. The basic idea is a follows. We set up a sequence of methodology. The basic idea is a follows. We set up a sequence of
evenly spaced times T1 < T2 < ... < Tn. Each time Ti is potentially evenly spaced times T1 < T2 < ... < Tn. Each time Ti is potentially
the first packet time for a packet pair measurement. We make an the first packet time for a packet pair measurement. We make an
independent random decision at each time, whether to initiate such a independent random decision at each time, whether to initiate such a
measurement. Hence the interval count between successive times at measurement. Hence, the interval count between successive times at
which a pair is initiated follows a geometric distribution. We also which a pair is initiated follows a geometric distribution. We also
specify that the spacing between successive times Ti is the same as specify that the spacing between successive times Ti is the same as
the spacing between packets in a given pair. Thus if pairs happen to the spacing between packets in a given pair. Thus, if pairs happen
be launched at the successive times Ti T(i+1), the second packet of to be launched at the successive times Ti and T(i+1), the second
the first pair is actually used as the first packet of the second packet of the first pair is actually used as the first packet of the
pair. second pair.
4.1. Metric Name 4.1. Metric Name
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream Type-P-One-way-Bi-Packet-Loss-Geometric-Stream
4.2. Metric Parameters 4.2. Metric Parameters
o Src, the IP address of a source host o Src, the IP address of a source host
o Dst, the IP address of a destination host o Dst, the IP address of a destination host
o T0, the randomly selected starting time [RFC3432] for periodic o T0, the randomly selected starting time [RFC3432] for periodic
launch opportunities launch opportunities
o d, the time spacing between potential launch times, Ti and Ti+1 o d, the time spacing between potential launch times, Ti and T(i+1)
o n, a count of potential measurement instants o n, a count of potential measurement instants
o q, a launch probability o q, a launch probability
o F, a selection function defining unambiguously the two packets o F, a selection function defining unambiguously the two packets
from the stream selected for the metric. from the stream selected for the metric
o P, the specification of the packet type, over and above the source o P, the specification of the packet type, over and above the source
and destination address and destination address
4.3. Metric Units 4.3. Metric Units
A set of Loss Pairs L1, L2, ..., Lm for some m <= n A set of Loss Pairs L1, L2, ..., Lm for some m <= n
4.4. Metric Definition 4.4. Metric Definition
for each i = 0, 1, ..., n-1 we form the potential measurement time Ti For each i = 0, 1, ..., n-1 we form the potential measurement time Ti
= T + i * d. With probability q, a packet pair measurement is = T0 + i*d. With probability q, a packet pair measurement is
launched at Ti, resulting in a Type-P-One-way-Bi-Packet-Loss with launched at Ti, resulting in a Type-P-One-way-Bi-Packet-Loss with
parameters (Src, Dst, Ti, Ti+1, Fi, P) where Fi is the restriction of parameters (Src, Dst, Ti, T(i+1), Fi, P) where Fi is the restriction
the selection function F to the packet pair at times Ti, Ti+1. L1, of the selection function F to the packet pair at times Ti, T(i+1).
L2,...Lm are the resulting Loss Pairs; m can be less than n since not L1, L2,...Lm are the resulting Loss Pairs; m can be less than n since
all time Ti have an associated measurement. not all times Ti have an associated measurement.
4.5. Discussion 4.5. Discussion
The above definition of Type-P-One-way-Bi-Packet-Loss-Geometric- The above definition of Type-P-One-way-Bi-Packet-Loss-Geometric-
Stream is equivalent to using Type-P-One-way-Bi-Packet-Loss-Stream Stream is equivalent to using Type-P-One-way-Bi-Packet-Loss-Stream
with an appropriate statistical definition of the selection function with an appropriate statistical definition of the selection function
F. F.
The number m of loss pairs in the metric can be less than the number The number m of Loss Pairs in the metric can be less than the number
of potential measurement instants because not all instants may of potential measurement instants because not all instants may
generate a probe when the launch probability q is strictly less than generate a probe when the launch probability q is strictly less than
1. 1.
4.6. Methodologies 4.6. Methodologies
The methodologies follow from: The methodologies follow from:
o the specific time T0, from which all successive Ti follow, and o the specific time T0, from which all successive Ti follow, and
skipping to change at page 13, line 21 skipping to change at page 12, line 27
Loss metric, a key source of error when emitting packets for Bi- Loss metric, a key source of error when emitting packets for Bi-
Packet Loss relates to resource limits on the host used to send the Packet Loss relates to resource limits on the host used to send the
packets. In particular, the choice of T0, the choice of the time packets. In particular, the choice of T0, the choice of the time
spacing, and the choice of the launch probability results in a spacing, and the choice of the launch probability results in a
schedule for sending packets. Insufficient CPU resources on the schedule for sending packets. Insufficient CPU resources on the
sending host may result in an inability to send packets according to sending host may result in an inability to send packets according to
schedule. Note that the choice of time spacing directly affects the schedule. Note that the choice of time spacing directly affects the
ability of the host CPU to meet the required schedule (e.g., consider ability of the host CPU to meet the required schedule (e.g., consider
a 100 microsecond spacing versus a 100 millisecond spacing). a 100 microsecond spacing versus a 100 millisecond spacing).
For other considerations, refer to Section 3.7. [RFC2680]. For other considerations, refer to Section 3.7 of [RFC2680].
4.8. Reporting the Metric 4.8. Reporting the Metric
Refer to Section 3.8. of [RFC2680]. Refer to Section 3.8. of [RFC2680].
5. Loss Episode Proto-Metrics 5. Loss Episode Proto-Metrics
This section describes four generic proto-metric quantities This section describes four generic proto-metric quantities
associated with an arbitrary set of loss pairs. These are the Loss- associated with an arbitrary set of Loss Pairs. These are the Loss-
Pair-Counts, Bi-Packet-Loss-Ratio, Bi-Packet-Loss-Episode-Duration- Pair-Counts, Bi-Packet-Loss-Ratio, Bi-Packet-Loss-Episode-Duration-
Number, Bi-Packet-Loss-Episode-Frequency-Number. Specific loss Number, Bi-Packet-Loss-Episode-Frequency-Number. Specific loss
episode metrics can then be constructed when these proto metrics take episode metrics can then be constructed when these proto-metrics
as their input, sets of loss pairs samples generated by the Type-P- take, as their input, sets of Loss Pairs samples generated by the
One-way-Bi-Packet-Loss-Stream and Type-P-One-way-Bi-Packet-Loss- Type-P-One-way-Bi-Packet-Loss-Stream and Type-P-One-way-Bi-Packet-
Geometric Stream. The second of these is described in Section 4. It Loss-Geometric-Stream. The second of these is described in
is not expected that these proto-metrics would be reported Section 4. It is not expected that these proto-metrics would be
themselves. Rather they are intermediate quantities in the reported themselves. Rather, they are intermediate quantities in the
production of the final metrics of Section 6 below, and could be production of the final metrics of Section 6 below, and could be
rolled up into them in implementations. The metrics report loss rolled up into metrics in implementations. The metrics report loss
episode durations and frequencies in terms of packet counts, since episode durations and frequencies in terms of packet counts, since
they do not depend on the actual time between probe packets. The they do not depend on the actual time between probe packets. The
final metrics of Section 6 incorporate timescales and yield durations final metrics of Section 6 incorporate timescales and yield durations
in seconds, and frequencies as per second. in seconds and frequencies as per second.
5.1. Loss-Pair-Counts 5.1. Loss-Pair-Counts
Loss-Pair-Counts are the absolute frequencies of the 4 types of loss Loss-Pair-Counts are the absolute frequencies of the four types of
pair outcome in a sample. More precisely, the Loss-Pair-Counts Loss Pair outcome in a sample. More precisely, the Loss-Pair-Counts
associated with a set of loss pairs L1,,,,Ln are the numbers N(i,j) associated with a set of Loss Pairs L1,,,,Ln are the numbers N(i,j)
of such loss pairs that take each possible value (i,j) in the set ( of such Loss Pairs that take each possible value (i,j) in the set (
(0,0), (0,1), (1,0), (1,1)). (0,0), (0,1), (1,0), (1,1)).
5.2. Bi-Packet-Loss-Ratio 5.2. Bi-Packet-Loss-Ratio
The Bi-Packet-loss-ratio associated with a set of n loss pairs The Bi-Packet-Loss-Ratio associated with a set of n Loss Pairs
L1,,,,Ln is defined in terms of their Loss-Pair-Counts by the L1,,,,Ln is defined in terms of their Loss-Pair-Counts by the
quantity (N(1,0) +N(1,1))/n. quantity (N(1,0) + N(1,1))/n.
Note this is formally equivalent to the loss metric Type-P-One-way- Note this is formally equivalent to the loss metric Type-P-One-way-
Packet-Loss-Average from[RFC2680] since it averages single packet Packet-Loss-Average from [RFC2680], since it averages single packet
losses. losses.
5.3. Bi-Packet-Loss-Episode-Duration-Number 5.3. Bi-Packet-Loss-Episode-Duration-Number
The Bi-Packet-Loss-Episode-Duration-Number associated with a set of n The Bi-Packet-Loss-Episode-Duration-Number associated with a set of n
loss pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts in Loss Pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts in
the following cases: the following cases:
o 2*(N(0,1) + N(1,0) + N(1,1)/ (N(0,1)+N(1,0)) - 1 if N(0,1) + o (2*N(1,1) + N(0,1) + N(1,0)) / (N(0,1) + N(1,0)) if N(0,1) +
N(1,0) >1 N(1,0) > 0
o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost) o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost)
o Undefined if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost) o Undefined if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost)
Note N(0,1) + N(1,0) is zero if there are no transitions between loss Note N(0,1) + N(1,0) is zero if there are no transitions between loss
and no-loss outcomes. and no-loss outcomes.
5.4. Bi-Packet-Loss-Episode-Frequency-Number 5.4. Bi-Packet-Loss-Episode-Frequency-Number
The Bi-Packet-Loss-Episode-Frequency-Number associated with a set of The Bi-Packet-Loss-Episode-Frequency-Number associated with a set of
n loss pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts n Loss Pairs L1,,,,Ln is defined in terms of their Loss-Pair-Counts
as Bi-Packet-Loss-Ratio / Bi-Packet-Loss-Episode-Duration-Number, as Bi-Packet-Loss-Ratio / Bi-Packet-Loss-Episode-Duration-Number,
when this can be defined, specifically, it is: when this can be defined, specifically, it is as follows:
o (N(1,0)+N(1,1)) * (N(0,1)+N(1,0)) / (2*N(1,1)+N(0,1)+N(1,0) ) / n o (N(1,0) + N(1,1)) * (N(0,1) + N(1,0)) / (2*N(1,1) + N(0,1) +
if N(0,1)+N(0,1) > 0 N(1,0) ) / n if N(0,1) + N(1,0) > 0
o 0 if N(0,1)+N(1,0) +N(1,1) = 0 (no probe packets lost) o 0 if N(0,1) + N(1,0) + N(1,1) = 0 (no probe packets lost)
o 1 if N(0,1) +N(1,0) +N(0,0) = 0 (all probe packets lost) o 1 if N(0,1) + N(1,0) + N(0,0) = 0 (all probe packets lost)
6. Loss Episode Metrics derived from Bi-Packet Loss Probing 6. Loss Episode Metrics Derived from Bi-Packet Loss Probing
Metrics for the time frequency and time duration of loss episodes are Metrics for the time frequency and time duration of loss episodes are
now defined as functions of set of n loss pairs L1,....,Ln. Although now defined as functions of the set of n Loss Pairs L1,....,Ln.
a loss episode is defined as a maximal set of successive lost Although a loss episode is defined as a maximal set of successive
packets, the loss episode metrics are not defined directly in terms lost packets, the loss episode metrics are not defined directly in
of the sequential patterns of packet loss exhibited by loss pairs. terms of the sequential patterns of packet loss exhibited by Loss
This is because samples, including Type-P-One-way-Bi-Packet-Loss- Pairs. This is because samples, including Type-P-One-way-Bi-Packet-
Geometric-Stream, generally do not report all lost packets in each Loss-Geometric-Stream, generally do not report all lost packets in
episode. Instead, the metrics are defined as functions of the Loss- each episode. Instead, the metrics are defined as functions of the
Pair-Counts of the sample, for reasons that are now described. Loss-Pair-Counts of the sample, for reasons that are now described.
Consider an idealized Type-P-One-way-Bi-Packet-Loss-Geometric-Stream Consider an idealized Type-P-One-way-Bi-Packet-Loss-Geometric-Stream
sample in which the launch probability q =1. It is shown in [SBDR08] sample in which the launch probability q =1. It is shown in [SBDR08]
that the average number of packets in a loss episode of this ideal that the average number of packets in a loss episode of this ideal
sample is exactly the Bi-Packet-Loss-Episode-Duration derived from sample is exactly the Bi-Packet-Loss-Episode-Duration derived from
its set of loss pairs. Note this computation makes no reference to its set of Loss Pairs. Note this computation makes no reference to
the position of lost packet in the sequence of probes. the position of lost packet in the sequence of probes.
A general Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with A general Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with
launch probability q < 1, independently samples, with probability q, launch probability q < 1, independently samples, with probability q,
each loss pair of an idealized sample. On average, the Loss-Pair- each Loss Pair of an idealized sample. On average, the Loss-Pair-
Counts (if normalized by the total number of pairs) will be the same Counts (if normalized by the total number of pairs) will be the same
as in the idealized sample. The loss episode metrics in the general as in the idealized sample. The loss episode metrics in the general
case are thus estimators of those for the idealized case; the case are thus estimators of those for the idealized case; the
statistical properties of this estimation, including a derivation of statistical properties of this estimation, including a derivation of
the estimation variance, is provided in [SBDR08]. the estimation variance, is provided in [SBDR08].
6.1. Geometric Stream: Loss Ratio 6.1. Geometric Stream: Loss Ratio
6.1.1. Metric Name 6.1.1. Metric Name
skipping to change at page 15, line 43 skipping to change at page 14, line 48
6.1.2. Metric Parameters 6.1.2. Metric Parameters
o Src, the IP address of a source host o Src, the IP address of a source host
o Dst, the IP address of a destination host o Dst, the IP address of a destination host
o T0, the randomly selected starting time [RFC3432] for periodic o T0, the randomly selected starting time [RFC3432] for periodic
launch opportunities launch opportunities
o d, the time spacing between potential launch times, Ti and Ti+1 o d, the time spacing between potential launch times, Ti and T(i+1)
o n, a count of potential measurement instants o n, a count of potential measurement instants
o q, a launch probability o q, a launch probability
o F, a selection function defining unambiguously the two packets o F, a selection function defining unambiguously the two packets
from the stream selected for the metric. from the stream selected for the metric
o P, the specification of the packet type, over and above the source o P, the specification of the packet type, over and above the source
and destination address and destination address
6.1.3. Metric Units 6.1.3. Metric Units
A decimal number in the interval [0,1] A decimal number in the interval [0,1]
6.1.4. Metric Definition 6.1.4. Metric Definition
skipping to change at page 16, line 26 skipping to change at page 15, line 30
parameters. parameters.
6.1.5. Discussion 6.1.5. Discussion
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio estimates the Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Ratio estimates the
fraction of packets lost from the geometric stream of Bi-Packet fraction of packets lost from the geometric stream of Bi-Packet
probes. probes.
6.1.6. Methodologies 6.1.6. Methodologies
Refer to Section 4.6 Refer to Section 4.6.
6.1.7. Errors and Uncertainties 6.1.7. Errors and Uncertainties
Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in
general (when the launch probability q <1) the metrics described in general (when the launch probability q <1), the metrics described in
this Section can be regarded as statistical estimators of the this section can be regarded as statistical estimators of the
corresponding idealized version corresponding to q = 1. Estimation corresponding idealized version corresponding to q = 1. Estimation
variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric- variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric-
Stream-Loss-Ratio is described in [SBDR08]. Stream-Loss-Ratio is described in [SBDR08].
For other issues refer to Section 4.7 For other issues, refer to Section 4.7
6.1.8. Reporting the Metric 6.1.8. Reporting the Metric
Refer to Section 4.8 Refer to Section 4.8.
6.2. Geometric Stream: Loss Episode Duration 6.2. Geometric Stream: Loss Episode Duration
6.2.1. Metric Name 6.2.1. Metric Name
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration
6.2.2. Metric Parameters 6.2.2. Metric Parameters
o Src, the IP address of a source host o Src, the IP address of a source host
o Dst, the IP address of a destination host o Dst, the IP address of a destination host
o T0, the randomly selected starting time [RFC3432] for periodic o T0, the randomly selected starting time [RFC3432] for periodic
launch opportunities launch opportunities
o d, the time spacing between potential launch times, Ti and Ti+1 o d, the time spacing between potential launch times, Ti and T(i+1)
o n, a count of potential measurement instants o n, a count of potential measurement instants
o q, a launch probability o q, a launch probability
o F, a selection function defining unambiguously the two packets o F, a selection function defining unambiguously the two packets
from the stream selected for the metric. from the stream selected for the metric
o P, the specification of the packet type, over and above the source o P, the specification of the packet type, over and above the source
and destination address and destination address
6.2.3. Metric Units 6.2.3. Metric Units
A non-negative number of seconds. A non-negative number of seconds
6.2.4. Metric Definition 6.2.4. Metric Definition
The result obtained by computing the Bi-Packet-Loss-Episode-Duration- The result obtained by computing the Bi-Packet-Loss-Episode-Duration-
Number over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample Number over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample
with the metric parameters, then multiplying the result by the launch with the metric parameters, then multiplying the result by the launch
spacing parameter d. spacing parameter d.
6.2.5. Discussion 6.2.5. Discussion
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Duration
estimates the average duration of a loss episode, measured in estimates the average duration of a loss episode, measured in
seconds. The duration measured in packets is obtained by dividing seconds. The duration measured in packets is obtained by dividing
the metric value by the packet launch spacing parameter d. the metric value by the packet launch spacing parameter d.
6.2.6. Methodologies 6.2.6. Methodologies
Refer to Section 4.6 Refer to Section 4.6.
6.2.7. Errors and Uncertainties 6.2.7. Errors and Uncertainties
Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in
general (when the launch probability q <1) the metrics described in general (when the launch probability q <1), the metrics described in
this Section can be regarded as statistical estimators of the this section can be regarded as statistical estimators of the
corresponding idealized version corresponding to q = 1. Estimation corresponding idealized version corresponding to q = 1. Estimation
variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric- variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric-
Stream-Episode-Duration is described in [SBDR08]. Stream-Episode-Duration is described in [SBDR08].
For other issues refer to Section 4.7 For other issues, refer to Section 4.7
6.2.8. Reporting the Metric 6.2.8. Reporting the Metric
Refer to Section 4.8 Refer to Section 4.8.
6.3. Geometric Stream: Loss Episode Frequency 6.3. Geometric Stream: Loss Episode Frequency
6.3.1. Metric Name 6.3.1. Metric Name
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency
6.3.2. Metric Parameters 6.3.2. Metric Parameters
o Src, the IP address of a source host o Src, the IP address of a source host
o Dst, the IP address of a destination host o Dst, the IP address of a destination host
o T0, the randomly selected starting time [RFC3432] for periodic o T0, the randomly selected starting time [RFC3432] for periodic
launch opportunities launch opportunities
o d, the time spacing between potential launch times, Ti and Ti+1 o d, the time spacing between potential launch times, Ti and T(i+1)
o n, a count of potential measurement instants o n, a count of potential measurement instants
o q, a launch probability o q, a launch probability
o F, a selection function defining unambiguously the two packets o F, a selection function defining unambiguously the two packets
from the stream selected for the metric. from the stream selected for the metric
o P, the specification of the packet type, over and above the source o P, the specification of the packet type, over and above the source
and destination address and destination address
6.3.3. Metric Units 6.3.3. Metric Units
A positive number. A positive number
6.3.4. Metric Definition 6.3.4. Metric Definition
The result obtained by computing the Bi-Packet-Loss-Episode-Frequency The result obtained by computing the Bi-Packet-Loss-Episode-
over a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream sample with the Frequency-Number over a Type-P-One-way-Bi-Packet-Loss-Geometric-
metric parameters, then dividing the result by the launch spacing Stream sample with the metric parameters, then dividing the result by
parameter d. the launch spacing parameter d.
6.3.5. Discussion 6.3.5. Discussion
Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency Type-P-One-way-Bi-Packet-Loss-Geometric-Stream-Episode-Frequency
estimates the average frequency per unit time with which loss estimates the average frequency per unit time with which loss
episodes start (or finish). The frequency relative to the count of episodes start (or finish). The frequency relative to the count of
potential probe launches is obtained by multiplying the metric value potential probe launches is obtained by multiplying the metric value
by the packet launch spacing parameter d. by the packet launch spacing parameter d.
6.3.6. Methodologies 6.3.6. Methodologies
Refer to Section 4.6 Refer to Section 4.6.
6.3.7. Errors and Uncertainties 6.3.7. Errors and Uncertainties
Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in Because Type-P-One-way-Bi-Packet-Loss-Geometric-Stream is sampled in
general (when the launch probability q <1) the metrics described in general (when the launch probability q <1), the metrics described in
this Section can be regarded as statistical estimators of the this section can be regarded as statistical estimators of the
corresponding idealized version corresponding to q = 1. Estimation corresponding idealized version corresponding to q = 1. Estimation
variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric- variance as it applies to Type-P-One-way-Bi-Packet-Loss-Geometric-
Stream-Episode-Frequency is described in [SBDR08]. Stream-Episode-Frequency is described in [SBDR08].
For other issues refer to Section 4.7 For other issues, refer to Section 4.7
6.3.8. Reporting the Metric 6.3.8. Reporting the Metric
Refer to Section 4.8 Refer to Section 4.8.
7. Applicability of Loss Episode Metrics 7. Applicability of Loss Episode Metrics
7.1. Relation to Gilbert Model 7.1. Relation to Gilbert Model
The general Gilbert-Elliot model is a discrete time Markov chain over The general Gilbert-Elliot model is a discrete time Markov chain over
two states, Good (g) and Bad (b), each with its own independent two states, Good (g) and Bad (b), each with its own independent
packet loss rate. In the simplest case, the Good loss rate is 0 packet loss ratio. In the simplest case, the Good loss ratio is 0,
while the Bad loss rate is 1. Correspondingly, there are two while the Bad loss ratio is 1. Correspondingly, there are two
independent parameters, the Markov transition probabilities P(g|b) = independent parameters, the Markov transition probabilities P(g|b) =
1- P(b|b) and P(b|g) = 1- P(g|g), where P(i|j) is the probability to 1- P(b|b) and P(b|g) = 1- P(g|g), where P(i|j) is the probability to
transition from state j and step n to state i at step n+1. With transition from state j and step n to state i at step n+1. With
these parameters, the fraction of steps spent in the bad state is these parameters, the fraction of steps spent in the bad state is
P(b|g)/(P(b|g) + P(g|b)) while the average duration of a sojourn in P(b|g)/(P(b|g) + P(g|b)), while the average duration of a sojourn in
the bad state is 1/P(g|b) steps. the bad state is 1/P(g|b) steps.
Now identify the steps of the Markov chain with the possible sending Now identify the steps of the Markov chain with the possible sending
times of packets for a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream times of packets for a Type-P-One-way-Bi-Packet-Loss-Geometric-Stream
with launch spacing d. Suppose the loss episode metrics Type-P-One- with launch spacing d. Suppose the loss episode metrics Type-P-One-
way-Bi-Packet-Loss-Geometric-Stream-Ratio and Type-P-One-way-Bi- way-Bi-Packet-Loss-Geometric-Stream-Ratio and Type-P-One-way-Bi-
Packet-Loss-Geometric-Stream-Episode-Duration take the values r and m Packet-Loss-Geometric-Stream-Episode-Duration take the values r and
respectively. Then from the discussion in Section 6.2.5 the m, respectively. Then, from the discussion in Section 6.1.5, the
following can be equated: following can be equated:
r = P(b|g)/(P(b|g) + P(g|b)) and m/d = 1/P(g|b). r = P(b|g)/(P(b|g) + P(g|b)) and m/d = 1/P(g|b).
These relationships can be inverted in order to recover the Gilbert These relationships can be inverted in order to recover the Gilbert
model parameters: model parameters:
P(g|b) = d/m and P(b|g)=d/m/(1/r - 1) P(g|b) = d/m and P(b|g)=d/m/(1/r - 1)
8. IPR Considerations 8. Security Considerations
An IPR disclosure concerning some of the material covered in this
document has been made to the IETF: see
https://datatracker.ietf.org/ipr/1354/
9. Security Considerations
Conducting Internet measurements raises both security and privacy Conducting Internet measurements raises both security and privacy
concerns. This memo does not specify an implementation of the concerns. This memo does not specify an implementation of the
metrics, so it does not directly affect the security of the Internet metrics, so it does not directly affect the security of the Internet
nor of applications which run on the Internet. or of applications that run on the Internet. However,implementations
However,implementations of these metrics must be mindful of security of these metrics must be mindful of security and privacy concerns.
and privacy concerns.
There are two types of security concerns: potential harm caused by There are two types of security concerns: potential harm caused by
the measurements, and potential harm to the measurements. The the measurements and potential harm to the measurements. The
measurements could cause harm because they are active, and inject measurements could cause harm because they are active and inject
packets into the network. The measurement parameters MUST be packets into the network. The measurement parameters MUST be
carefully selected so that the measurements inject trivial amounts of carefully selected so that the measurements inject trivial amounts of
additional traffic into the networks they measure. If they inject additional traffic into the networks they measure. If they inject
"too much" traffic, they can skew the results of the measurement, and "too much" traffic, they can skew the results of the measurement and,
in extreme cases cause congestion and denial of service. The in extreme cases, cause congestion and denial of service. The
measurements themselves could be harmed by routers giving measurement measurements themselves could be harmed by routers giving measurement
traffic a different priority than "normal" traffic, or by an attacker traffic a different priority than "normal" traffic, or by an attacker
injecting artificial measurement traffic. If routers can recognize injecting artificial measurement traffic. If routers can recognize
measurement traffic and treat it separately, the measurements may not measurement traffic and treat it separately, the measurements may not
reflect actual user traffic. If an attacker injects artificial reflect actual user traffic. If an attacker injects artificial
traffic that is accepted as legitimate, the loss rate will be traffic that is accepted as legitimate, the loss rate will be
artificially lowered. Therefore, the measurement methodologies artificially lowered. Therefore, the measurement methodologies
SHOULD include appropriate techniques to reduce the probability that SHOULD include appropriate techniques to reduce the probability that
measurement traffic can be distinguished from "normal" traffic. measurement traffic can be distinguished from "normal" traffic.
Authentication techniques, such as digital signatures, may be used Authentication techniques, such as digital signatures, may be used
where appropriate to guard against injected traffic attacks. The where appropriate to guard against injected traffic attacks. The
privacy concerns of network measurement are limited by the active privacy concerns of network measurement are limited by the active
measurements described in this memo: they involve no release of user measurements described in this memo: they involve no release of user
data. data.
10. IANA Considerations 9. References
This document requests no actions from IANA.
11. Acknowledgements
12. References
12.1. Normative References 9.1. Normative References
[RFC2680] Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way [RFC2680] Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way
Packet Loss Metric for IPPM", RFC 2680, September 1999. Packet Loss Metric for IPPM", RFC 2680, September 1999.
[RFC3393] Demichelis, C. and P. Chimento, "IP Packet Delay Variation [RFC3393] Demichelis, C. and P. Chimento, "IP Packet Delay Variation
Metric for IP Performance Metrics (IPPM)", RFC 3393, Metric for IP Performance Metrics (IPPM)", RFC 3393,
November 2002. November 2002.
[RFC3611] Friedman, T., Caceres, R., and A. Clark, "RTP Control [RFC3611] Friedman, T., Caceres, R., and A. Clark, "RTP Control
Protocol Extended Reports (RTCP XR)", RFC 3611, Protocol Extended Reports (RTCP XR)", RFC 3611,
November 2003. November 2003.
[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.
[RFC3432] Raisanen, V., Grotefeld, G., and A. Morton, "Network [RFC3432] Raisanen, V., Grotefeld, G., and A. Morton, "Network
performance measurement with periodic streams", RFC 3432, performance measurement with periodic streams", RFC 3432,
November 2002. November 2002.
12.2. Informative References 9.2. Informative References
[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.
[RFC3357] Koodli, R. and R. Ravikanth, "One-way Loss Pattern Sample [RFC3357] Koodli, R. and R. Ravikanth, "One-way Loss Pattern Sample
Metrics", RFC 3357, August 2002. Metrics", RFC 3357, August 2002.
[SBDR08] IEEE/ACM Transactions on Networking, 16(2): 307-320, "A [SBDR08] IEEE/ACM Transactions on Networking, 16(2): 307-320, "A
Geometric Approach to Improving Active Packet Loss Geometric Approach to Improving Active Packet Loss
skipping to change at page 22, line 19 skipping to change at page 21, line 15
Authors' Addresses Authors' Addresses
Nick Duffield Nick Duffield
AT&T Labs-Research AT&T Labs-Research
180 Park Avenue 180 Park Avenue
Florham Park, NJ 07932 Florham Park, NJ 07932
USA USA
Phone: +1 973 360 8726 Phone: +1 973 360 8726
Fax: +1 973 360 8871 Fax: +1 973 360 8871
Email: duffield@research.att.com EMail: duffield@research.att.com
URI: http://www.research.att.com/people/Duffield_Nicholas_G URI: http://www.research.att.com/people/Duffield_Nicholas_G
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/
Joel Sommers Joel Sommers
Colgate University Colgate University
304 McGregory Hall 304 McGregory Hall
Hamilton, NY 13346 Hamilton, NY 13346
USA USA
Phone: +1 315 228 7587 Phone: +1 315 228 7587
Fax: Fax:
Email: jsommers@colgate.edu EMail: jsommers@colgate.edu
URI: http://cs.colgate.edu/faculty/jsommers URI: http://cs.colgate.edu/faculty/jsommers
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