 1/draftietfippmmultimetrics02.txt 20070307 00:12:54.000000000 +0100
+++ 2/draftietfippmmultimetrics03.txt 20070307 00:12:54.000000000 +0100
@@ 1,21 +1,21 @@
Network Working Group E. Stephan
InternetDraft France Telecom
Intended status: Informational L. Liang
Expires: April 25, 2007 University of Surrey
+Expires: September 2, 2007 University of Surrey
A. Morton
AT&T Labs
 October 22, 2006
+ March 1, 2007
IP Performance Metrics (IPPM) for spatial and multicast
 draftietfippmmultimetrics02
+ draftietfippmmultimetrics03
Status of this Memo
By submitting this InternetDraft, each author represents that any
applicable patent or other IPR claims of which he or she is aware
have been or will be disclosed, and any of which he or she becomes
aware will be disclosed, in accordance with Section 6 of BCP 79.
InternetDrafts are working documents of the Internet Engineering
Task Force (IETF), its areas, and its working groups. Note that
@@ 26,123 +26,134 @@
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use InternetDrafts as reference
material or to cite them other than as "work in progress."
The list of current InternetDrafts can be accessed at
http://www.ietf.org/ietf/1idabstracts.txt.
The list of InternetDraft Shadow Directories can be accessed at
http://www.ietf.org/shadow.html.
 This InternetDraft will expire on April 25, 2007.
+ This InternetDraft will expire on September 2, 2007.
Copyright Notice
 Copyright (C) The Internet Society (2006).
+ Copyright (C) The IETF Trust (2007).
Abstract
The IETF IP Performance Metrics (IPPM) working group has standardized
metrics for measuring endtoend performance between 2 points. This
memo defines 2 sets of metrics to extend these endtoend ones. It
defines spatial metrics for measuring the performance of segments
along a path and metrics for measuring the performance of a group of
users in multiparty communications.
Table of Contents
 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 5
 2.1. Multiparty metric . . . . . . . . . . . . . . . . . . . . 5
 2.2. Spatial metric . . . . . . . . . . . . . . . . . . . . . . 5
 2.3. Spatial metric points of interest . . . . . . . . . . . . 5
 2.4. Onetogroup metric . . . . . . . . . . . . . . . . . . . 5
 2.5. Onetogroup metric points of interest . . . . . . . . . . 5
 2.6. Reference point . . . . . . . . . . . . . . . . . . . . . 5
 2.7. Vector . . . . . . . . . . . . . . . . . . . . . . . . . . 6
 2.8. Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . 6
 3. Motivations for spatial and onetogroup metrics . . . . . . . 7
 3.1. spatial metrics . . . . . . . . . . . . . . . . . . . . . 7
 3.2. Onetogroup metrics . . . . . . . . . . . . . . . . . . . 8
 3.3. Discussion on Grouptoone and Grouptogroup metrics . . 9
 4. Spatial metrics definitions . . . . . . . . . . . . . . . . . 9
+ 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 4
+ 2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 6
+ 2.1. Multiparty metric . . . . . . . . . . . . . . . . . . . . 6
+ 2.2. Spatial metric . . . . . . . . . . . . . . . . . . . . . . 6
+ 2.3. Spatial metric points of interest . . . . . . . . . . . . 6
+ 2.4. Onetogroup metric . . . . . . . . . . . . . . . . . . . 6
+ 2.5. Onetogroup metric points of interest . . . . . . . . . . 6
+ 2.6. Reference point . . . . . . . . . . . . . . . . . . . . . 6
+ 2.7. Vector . . . . . . . . . . . . . . . . . . . . . . . . . . 7
+ 2.8. Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . 7
+ 3. Motivations for spatial and onetogroup metrics . . . . . . . 8
+ 3.1. spatial metrics . . . . . . . . . . . . . . . . . . . . . 8
+ 3.2. Onetogroup metrics . . . . . . . . . . . . . . . . . . . 9
+ 3.3. Discussion on Grouptoone and Grouptogroup metrics . . 10
+ 4. Spatial metrics definitions . . . . . . . . . . . . . . . . . 10
4.1. A Definition for Spatial Oneway Delay Vector . . . . . . 10
 4.2. A Definition of a sample of Oneway Delay of a sub path . 12
 4.3. A Definition for Spatial Oneway Packet Loss Vector . . . 15
 4.4. A Definition for Spatial Oneway Jitter Vector . . . . . . 16
 4.5. Pure Passive Metrics . . . . . . . . . . . . . . . . . . . 18
 4.6. Discussion on spatial statistics . . . . . . . . . . . . . 20
 5. Onetogroup metrics definitions . . . . . . . . . . . . . . . 20
 5.1. A Definition for onetogroup Oneway Delay . . . . . . . 20
 5.2. A Definition for onetogroup Oneway Packet Loss . . . . 21
 5.3. A Definition for onetogroup Oneway Jitter . . . . . . . 21
 5.4. Discussion on onetogroup statistics . . . . . . . . . . 23
 6. Extension from onetoone to onetomany measurement . . . . . 26
 7. Open issues . . . . . . . . . . . . . . . . . . . . . . . . . 27
 8. Security Considerations . . . . . . . . . . . . . . . . . . . 27
 9. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 27
 10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 27
 11. References . . . . . . . . . . . . . . . . . . . . . . . . . . 28
 11.1. Normative References . . . . . . . . . . . . . . . . . . . 28
 11.2. Informative References . . . . . . . . . . . . . . . . . . 28
 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 29
 Intellectual Property and Copyright Statements . . . . . . . . . . 30
+ 4.2. A Definition of a sample of Oneway Delay of a sub path . 13
+ 4.3. A Definition for Spatial Oneway Packet Loss Vector . . . 16
+ 4.4. A Definition for Spatial Oneway Jitter Vector . . . . . . 17
+ 4.5. Pure Passive Metrics . . . . . . . . . . . . . . . . . . . 19
+ 4.6. Discussion on spatial statistics . . . . . . . . . . . . . 21
+ 5. Onetogroup metrics definitions . . . . . . . . . . . . . . . 21
+ 5.1. A Definition for onetogroup Oneway Delay . . . . . . . 21
+ 5.2. A Definition for onetogroup Oneway Packet Loss . . . . 22
+ 5.3. A Definition for onetogroup Oneway Jitter . . . . . . . 22
+ 6. OnetoGroup Sample Statistics . . . . . . . . . . . . . . . . 24
+ 6.1. Discussion on the Impact of packet loss on statistics . . 26
+ 6.2. General Metric Parameters . . . . . . . . . . . . . . . . 27
+ 6.3. OnetoGroup oneway Delay Statistics . . . . . . . . . . 28
+ 6.4. OnetoGroup oneway Loss Statistics . . . . . . . . . . . 31
+ 6.5. OnetoGroup oneway Delay Variation Statistics . . . . . 33
+ 7. Measurement Methods: Scaleability and Reporting . . . . . . . 33
+ 7.1. Computation methods . . . . . . . . . . . . . . . . . . . 34
+ 7.2. Measurement . . . . . . . . . . . . . . . . . . . . . . . 35
+ 7.3. effect of Time and Space Aggregation Order on Group
+ Stats . . . . . . . . . . . . . . . . . . . . . . . . . . 35
+ 7.4. effect of Time and Space Aggregation Order on Spatial
+ Stats . . . . . . . . . . . . . . . . . . . . . . . . . . 37
+ 8. Open issues . . . . . . . . . . . . . . . . . . . . . . . . . 37
+ 9. Security Considerations . . . . . . . . . . . . . . . . . . . 37
+ 9.1. passive measurement . . . . . . . . . . . . . . . . . . . 37
+ 9.2. onetogroup metric . . . . . . . . . . . . . . . . . . . 37
+ 10. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 37
+ 11. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 38
+ 12. References . . . . . . . . . . . . . . . . . . . . . . . . . . 42
+ 12.1. Normative References . . . . . . . . . . . . . . . . . . . 42
+ 12.2. Informative References . . . . . . . . . . . . . . . . . . 43
+ Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 43
+ Intellectual Property and Copyright Statements . . . . . . . . . . 45
1. Introduction
The metrics specified in this memo are built on notions introduced
and discussed in the IPPM Framework document, RFC 2330 [RFC2330].
The reader should be familiar with these documents.
This memo makes use of definitions of endtoend Oneway Delay
Metrics defined in the RFC 2679 [RFC2679] to define metrics for
decomposition of endtoend oneway delays measurements.
This memo makes use of definitions of endtoend Oneway Packet loss
Metrics defined in the RFC 2680 [RFC2680] to define metrics for
decomposition of endtoend oneway packet loss measurements.
The IPPM WG defined a framework for metric definitions and endtoend
measurements:
o A general framework for defining performance metrics, described in
 the Framework for IP Performance Metrics, RFC 2330 [RFC2330];
+ the Framework for IP Performance Metrics [RFC2330];
 o A Oneway Active Measurement Protocol Requirements, RFC 3763
 [RFC3763];
+ o A Oneway Active Measurement Protocol Requirements [RFC3763];
 o A Oneway Active Measurement Protocol (OWAMP) [work in progress];
+ o A Oneway Active Measurement Protocol (OWAMP) [RFC4656];
 o An IP Performance Metrics Registry , RFC 4148 [RFC4148];
+ o An IP Performance Metrics Registry [RFC4148];
It specified a set of endtoend metrics, which conform to this
framework:
 o The IPPM Metrics for Measuring Connectivity, RFC 2678 [RFC2678];
+ o The IPPM Metrics for Measuring Connectivity [RFC2678];
 o The Oneway Delay Metric for IPPM, RFC 2679 [RFC2679];
+ o The Oneway Delay Metric for IPPM [RFC2679];
 o The Oneway Packet Loss Metric for IPPM, RFC 2680 [RFC2680];
+ o The Oneway Packet Loss Metric for IPPM [RFC2680];
 o The Roundtrip Delay Metric for IPPM, RFC 2681 [RFC2681];
+ o The Roundtrip Delay Metric for IPPM [RFC2681];
o A Framework for Defining Empirical Bulk Transfer Capacity Metrics
 RFC 3148 [RFC3148];
+ [RFC3148];
 o Oneway Loss Pattern Sample Metrics, RFC 3357 [RFC3357];
+ o Oneway Loss Pattern Sample Metrics [RFC3357];
 o IP Packet Delay Variation Metric for IPPM, RFC 3393 [RFC3393];
+ o IP Packet Delay Variation Metric for IPPM [RFC3393];
 o Network performance measurement for periodic streams, RFC 3432
 [RFC3432];
 o Packet Reordering Metric for IPPM [Work in progress];
+ o Network performance measurement for periodic streams [RFC3432];
+ o Packet Reordering Metric for IPPM [RFC4737][Work in progress];
Based on these works, this memo defines 2 kinds of multi party
metrics.
Firstly it defines spatial metrics:
o A 'sample', called TypePSpatialOnewayDelayVector, will be
introduced to divide an endtoend TypePOnewayDelay in a
spatial sequence of oneway delays.
o A 'sample', called TypePSpatialOnewayPacketLossVector, will
@@ 200,21 +212,21 @@
2.2. Spatial metric
A metric is said to be spatial if one of the hosts involved is
neither the source nor the destination of the metered packet.
2.3. Spatial metric points of interest
Points of interest of a spatial metric are the routers or sibling in
the path between source and destination (in addition to the source
 and the destination themself).
+ and the destination themselves).
2.4. Onetogroup metric
A metric is said to be onetogroup if the measured packet is sent by
one source and (potentially) received by several destinations. Thus,
the topology of the communication group can be viewed as a centre
distributed or serverclient topology with the source as the centre/
server in the topology.
2.5. Onetogroup metric points of interest
@@ 235,106 +247,97 @@
calculation will be carried out.
2.7. Vector
A group of singletons is the set of results of the observation of the
behaviour of the same packet at different places of a network.
A Vector is a set of singletons, which are a set of results of the
observation of the behaviour of the same packet at different places
of a network at different time. For instance, if Oneway delay
 singletons abserved at N receivers for Packet P sent by the source
+ singletons observed at N receivers for Packet P sent by the source
Src are dT1, dT2,..., dTN, it can be say that a vector V with N
 elements can be orgnized as {dT1, dT2,..., dTN}. The elements in one
 vector are singletons distinct with each other in terms of both
+ elements can be organized as {dT1, dT2,..., dTN}. The elements in
+ one vector are singletons distinct with each other in terms of both
measurement point and time. Given the vector V as an example, the
element dT1 is distinct from the rest by measured at receiver 1 at
time T1. Additional to a singleton, Vector gives information over a
space dimension.
2.8. Matrix
 Several vectors can orgnize form up a Matrix, which contains results
+ Several vectors can organize form up a Matrix, which contains results
observed in a sampling interval at different place of a network at
different time. For instance, given Oneway delay vectors V1={dT11,
dT12,..., dT1N}, V2={dT21, dT22,..., dT2N},..., Vm={dTm1, dTm2,...,
dTmN} for Packet P1, P2,...,Pm, we can have a Oneway delay Matrix
{V1, V2,...,Vm}. Additional to the information given by a Vector, a
Matrix is more powerful to present network performance in both space
 and time dimensions. It normally corresponding to a sample.
+ and time dimensions. It normally corresponds to a sample.
The relation among Singleton, Vector and Matrix can be shown in the
 following Fig 1.
+ following Figure 1.
 one to group Singleton
+ onetogroup Singleton
/ Sample
 Src Rcvr ..............................
 ..................R1dT1 R1dT2 R1dT3 R1dT4
+ Src Recv ..............................
+ .................... 1 R1dT1 R1dT2 R1dT3 R1dT4
`:=.._
T `._ ``..__
 `. ` R2dT1 R2dT2 R2dT3 R2dT4
+ `. `... 2 R2dT1 R2dT2 R2dT3 R2dT4
`.
`.
 `._R3dT1 R3dT2 R3dT3 R3dT4
+ `.... N R3dT1 R3dT2 R3dT3 R3dT4
Vector Matrix
(space) (time)
 Figure 1.
+ Figure 1: Relation beween Singletons, vectors and matrix
3. Motivations for spatial and onetogroup metrics
All IPPM metrics are defined for endtoend measurement. These
metrics provide very good guides for measurement in the pair
communications. However, further efforts should be put to define
metrics for multiparty measurements such as one to one trajectory
metrics and one to multipoint metrics.
3.1. spatial metrics
Decomposition of instantaneous endtoend measures is needed:
 o The PCE WG is extending existing protocols to permit remote path
 computation and path computation quality, including inter domain.
 One may say that in intra domain the decomposing the performance
 of a path is not whished. However such decomposition is desirable
 in interdomain to qualify each AS computation with the initial
 request. So it is necessary to define standard spatial metrics
 before going further in the computation of inter domain path with
 QoS constraint.
+ o Decomposing the performance of interdomain path is desirable in
+ interdomain to qualify per AS contribution to the performance. So
+ it is necessary to define standard spatial metrics before going
+ further in the computation of inter domain path with QoS
+ constraint.
o Traffic engineering and troubleshooting applications require
spatial views of the oneway delay consumption, identification of
the location of the lost of packets and the decomposition of the
jitter over the path.
o Monitoring the QoS of a multicast tree, of MPLS pointto
multipoint and interdomain communication require spatial
decomposition of the oneway delay, of the packet loss and of the
jitter.
o Composition of metrics is a need to scale in the measurement
 plane. The definition of composition metrics is a work in
 progress [ID.ietfippmspatialcomposition]; . Spatial measure
 give typically the individual performance of an intra domain
 segment. It is the elementary piece of information to exchange
 for measuring interdomain performance based on composition of
 metrics.
+ plane. Spatial measure give typically the individual performance
+ of an intra domain segment. It is the elementary piece of
+ information to exchange for measuring interdomain performance
+ based on composition of metrics.
o The PSAMP WG defines capabilities to sample packets in a way to to
 support measurement. [ID.boschiipfixreducingredundancy];
 defines a method to collect packets information to measure the
 instantaneous spatial performance without injecting test traffic.
 Consequently it is urgent to define a set of common spatial
 metrics for passive and active techniques which respect the IPPM
 framework [RFC2330]. This need is emphases by the fact that end
 toend spatial measurement involves the 2 techniques;
+ support instantaneous measurement respecful of the IPPM framework
+ [RFC2330]. Consequently it is necessary to define a set of
+ spatial metrics for passive and active techniques.
3.2. Onetogroup metrics
While the nodetonode based spatial measures can provide very useful
data in the view of each connection, we also need measures to present
the performance of a multiparty communication in the view of a group
with consideration that it involves a group of people rather than
two. As a consequence a simple oneway metric cannot describe the
multiconnection situation. We need some new metrics to collect
performance of all the connections for further statistics analysis.
@@ 360,20 +364,28 @@
the multiparty communications.
To understand the connection situation between one source and any one
receiver in the multiparty communication group, we need the
collection of instantaneous endtoend measures. It will give us
very detailed insight into each branch of the multicast tree in terms
of endtoend absolute QoS. It can provide clear and helpful
information for engineers to identify the connection with problems in
a complex multiparty routing tree.
+ The onetogroup metrics described in this memo introduce onetomany
+ concerns to the IPPM working group to measure the performance of a
+ group of users who receiving data from the same source. The concept
+ extends the "path" in the oneway measurement to "path tree" to cover
+ both onetoone and onetomany communications. Nevertheless,
+ applied to onetoone communications they provide exactly the same
+ results as the corresponding onetoone metrics.
+
3.3. Discussion on Grouptoone and Grouptogroup metrics
We note that points of interest can also be selected to define
measurements on Grouptoone and Grouptogroup topologies. These
topologies are currently beyond the scope of this memo, because they
would involve multiple packets launched from different sources.
However, we can give some clues here on these two cases.
The measurements for grouptoone topology can be easily derived from
the onetogroup measurement. The measurement point is the reference
@@ 391,22 +403,23 @@
onetogroup communications as < ha, Ha, Hb, Hc, ..., Hm >, < hb, Ha,
Hb, Hc, ..., Hm >, , ..., < hn, Ha, Hb, Hc,
..., Hm >.
4. Spatial metrics definitions
Spatial decomposition metrics are based on standard endtoend
metrics.
The definition of a spatial metric is coupled with the corresponding
 endtoend metric. The methodoly is based on the measure of the same
 test packet and parameters of the corresponding endtoend metric.
+ endtoend metric. The methodology is based on the measure of the
+ same test packet and parameters of the corresponding endtoend
+ metric.
4.1. A Definition for Spatial Oneway Delay Vector
This section is coupled with the definition of TypePOnewayDelay.
When a parameter from section 3 of [RFC2679] is first used in this
section, it will be tagged with a trailing asterisk.
Sections 3.5 to 3.8 of [RFC2679] give requirements and applicability
statements for endtoend onewaydelay measurements. They are
applicable to each point of interest Hi involved in the measure.
@@ 463,24 +476,23 @@
4.1.5. Discussion
Following are specific issues which may occur:
o the delay looks to decrease: dTi > DTi+1. this seem typically du
to some clock synchronisation issue. this point is discussed in
the section 3.7.1. "Errors or uncertainties related to Clocks" of
of [RFC2679];
o The location of the point of interest in the device influences the
 result (see [ID.quittekipfixmiddlebox]). If the packet is not
 observed on the input interface the delay includes buffering time
 and consequently an uncertainty due to the difference between
 'wire time' and 'host time';
+ result. If the packet is not observed on the input interface the
+ delay includes buffering time and consequently an uncertainty due
+ to the difference between 'wire time' and 'host time';
4.1.6. Interference with other test packet
To avoid packet collision it is preferable to include a sequence
number in the packet.
4.1.7. loss threshold
To determine if a dTi is defined or undefined it is necessary to
define a period of time after which a packet is considered loss.
@@ 508,21 +519,21 @@
It is out of the scope of this document to define how each Hi detects
the packet.
4.1.9. Reporting the metric
Section 3.6 of [RFC2679] indicates the items to report.
4.1.10. Path
It is clear that a endtoend TypePOnewayDelay can't determine
 the list of hosts the packet passes throught. Section 3.8.4 of
+ the list of hosts the packet passes through. Section 3.8.4 of
[RFC2679] says that the path traversed by the packet SHOULD be
reported but is practically impossible to determine.
This part of the job is provide by TypePSpatialOnewayDelay
Vector metric because each points of interest Hi which capture the
packet is part of the path.
4.2. A Definition of a sample of Oneway Delay of a sub path
This metric is similar to the metric TypePOnewayDelayPoisson
@@ 598,30 +609,29 @@
o When b is Dst is the measure of the last hop.
o the delay looks to decrease: dTi > DTi+1:
* This is typically du to clock synchronisation issue. this point
is discussed in the section 3.7.1. "Errors or uncertainties
related to Clocks" of of [RFC2679];
* This may occurs too when the clock resolution of one probe is
 bigger than the minimun delay of a path. As an example this
+ bigger than the minimum delay of a path. As an example this
happen when measuring the delay of a path which is 500 km long
with one probe synchronized using NTP having a clock resolution
of 8ms.
o The location of the point of interest in the device influences the
 result (see [ID.quittekipfixmiddlebox]). If the packet is not
 observed on the input interface the delay includes buffering time
 and consequently an uncertainty due to the difference between
 'wire time' and 'host time';
+ result. If the packet is not observed on the input interface the
+ delay includes buffering time and consequently an uncertainty due
+ to the difference between 'wire time' and 'host time';
o dTk.b may be observed and not dTk.a.
o Tk is unknown if the flow is made of end user packets, that is
pure passive measure. In this case Tk may be forced to Tk+dTk.a.
This motivate separate metrics names for pure passive measurement
or specific reporting information.
o Pure passive measure should consider packets of the same size and
of the same TypeP.
@@ 646,21 +656,21 @@
4.3. A Definition for Spatial Oneway Packet Loss Vector
This section is coupled with the definition of TypePOnewayPacket
Loss. Then when a parameter from the section 2 of [RFC2680] is first
used in this section, it will be tagged with a trailing asterisk.
Sections 2.5 to 2.8 of [RFC2680] give requirements and applicability
statements for endtoend onewayPacketLoss measurements. They are
applicable to each point of interest Hi involved in the measure.
Spatial packet loss measurement SHOULD be respectful of them,
 especially those related to methodology, clock, uncertainities and
+ especially those related to methodology, clock, uncertainties and
reporting.
Following we define the spatial metric, then we adapt some of the
points above and introduce points specific to spatial measurement.
4.3.1. Metric Name
TypePSpatialOnewayPacketLossVector
4.3.2. Metric Parameters
@@ 675,41 +685,41 @@
+ T*, a time, the sending (or initial observation) time for
a measured packet.
+ dT1,..., dTn, dT, a list of delay.
+ P*, the specification of the packet type.
+ , a path digest.
 + B1, B2, ..., Bi, ..., Bn, a list of boolean values.
+ + B1, B2, ..., Bi, ..., Bn, a list of Boolean values.
4.3.3. Metric Units
 A sequence of boolean values.
+ A sequence of Boolean values.
4.3.4. Definition
Given a TypeP packet sent by the sender Src at time T to the
receiver Dst in the path . Given the sequence of
times the packet passes ,
TypePOnewayPacketLostVector metric is defined as the sequence
of values such that for each Hi of the path, a
value of Bi of 0 means that dTi is a finite value, and a value of 1
means that dTi is undefined.
4.3.5. Discussion
 Following are specific issues wich may occur:
+ Following are specific issues which may occur:
o the result includes the sequence 1,0. This case means that the
packet was seen by a host but not by it successor on the path;
o
The location of the meter in the device influences the result:
o Even if the packet is received by a device, it may be not observed
by a meter located after a buffer;
@@ 721,21 +731,21 @@
4.4. A Definition for Spatial Oneway Jitter Vector
This section uses parameters from the definition of TypePOneway
ipdv. When a parameter from section 2 of [RFC3393] is first used in
this section, it will be tagged with a trailing asterisk.
Sections 3.5 to 3.7 of [RFC3393] give requirements and applicability
statements for endtoend onewayipdv measurements. They are
applicable to each point of interest Hi involved in the measure.
Spatial onewayipdv measurement SHOULD be respectful of them,
 especially those related to methodology, clock, uncertainities and
+ especially those related to methodology, clock, uncertainties and
reporting.
Following we adapt some of them and introduce points specific to
spatial measurement.
4.4.1. Metric Name
TypePSpatialOnewayJitterVector
4.4.2. Metric Parameters
@@ 800,28 +810,27 @@
at least one of them never passes Hi. T2T1 is the interpacket
emission interval and dT2dT1 is ddT* the TypePOnewayipdv at
T1,T2*.
4.4.5. Sections in progress
See sections 3.5 to 3.7 of [RFC3393].
4.5. Pure Passive Metrics
 Spatial metrics may be measured without injecting test traffic as
 described in [ID.boschiipfixreducingredundancy] .
+ Spatial metrics may be measured without injecting test traffic.
4.5.1. Discussion on Passive measurement
One might says that most of the operational issues occur in the last
mile and that consequently such measure are less useful than active
 measuremeent. Nevertheless they are usable for network TE and
+ measurement. Nevertheless they are usable for network TE and
interdomain QoS monitoring, and composition of metric.
Such a technique have some limitations that are discussed below.
4.5.1.1. Passive One way delay
As the packet is not a test packet, it does not include the time it
was sent.
Consequently a point of interest Hi ignores the time the packet was
@@ 846,29 +855,29 @@
An alternative to these issues consist in considering sample spatial
Oneway delay that T is the time when H1 (the first passive probe of
the path) observed the packet.
4.5.2. Reporting and composition
To avoid misunderstanding and to address specific reporting
constraint a proposal consists in defining distinct metrics for pure
passive measurement based on the definition above.
 It is crucial to know the methodologie used because of the difference
 of method of detection (expecting Seq++); because of the difference
 of source of time (H1 vs Src) and because of the difference of
 behavior of the source (Poisson/unknown).
+ It is crucial to know the methodologies used because of the
+ difference of method of detection (expecting Seq++); because of the
+ difference of source of time (H1 vs Src) and because of the
+ difference of behaviour of the source (Poisson/unknown).
4.5.3. naming and registry
Having distinct metrics identifiers for spatial metrics and passive
 spatial metrics in the [RFC4148] will avoid interoperabily issues
+ spatial metrics in the [RFC4148] will avoid interoperability issues
especially during composition of metrics.
4.5.4. Passive One way delay metrics
4.5.5. Passive One way PacketLoss metrics
4.5.6. Passive One way jitter metrics
4.6. Discussion on spatial statistics
@@ 990,130 +999,121 @@
singletons metrics TypePOnewayipdv [RFC3393].
5.3.4. Definition
Given a Type P packet stream, TypePonetogroupOnewayJitter
Vector is defined for two packets from the source Src to the N hosts
{Recv1,...,RecvN },which are selected by the selection function F, as
the difference between the value of the TypePonetogroupOneway
DelayVector from Src to { Recv1,..., RecvN } at time T1 and the
value of the TypePonetogroup OnewayDelayVector from Src to {
 Recv1,...,RecvN } at time T2. T1 is the wiretime at which Scr sent
+ Recv1,...,RecvN } at time T2. T1 is the wiretime at which Src sent
the first bit of the first packet, and T2 is the wiretime at which
Src sent the first bit of the second packet. This metric is derived
from the TypePoneto groupOnewayDelayVector metric.
Therefore, for a set of real number {ddT1,...,ddTn},TypePone to
groupOnewayJitterVector from Src to { Recv1,...,RecvN } at T1, T2
is {ddT1,...,ddTn} means that Src sent two packets, the first at
wiretime T1 (first bit), and the second at wiretime T2 (first bit)
and the packets were received by { Recv1,...,RecvN } at wiretime
{dT1+T1,...,dTn+T1}(last bit of the first packet), and at wiretime
{dT'1+T2,...,dT'n+T2} (last bit of the second packet), and that
{dT'1dT1,...,dT'ndTn} ={ddT1,...,ddTn}.
5.4. Discussion on onetogroup statistics
+6. OnetoGroup Sample Statistics
The defined onetogroup metrics above can all be directly achieved
from the relevant unicast oneway metrics. They managed to collect
all unicast measurement results of oneway metrics together in one
profile and sort them by receivers and packets in a multicast group.
They can provide sufficient information regarding the network
performance in terms of each receiver and guide engineers to identify
potential problem happened on each branch of a multicast routing
tree. However, these metrics can not be directly used to
conveniently present the performance in terms of a group and neither
to identify the relative performance situation.
 One may say that no matter how many people join the communication,
 the connections can still be treated as a set of onetoone
 connection. However, we might not describe a multiparty
 communication by a set of oneway measurement metrics because of the
 difficulty for understanding and the lack of convenience. For
 instance, an engineer might not describe the connections of a
 multiparty online conference in terms of onetogroup oneway delay
 for user A and B, B and C, and C and A because people might be
 confused. If there are more users in the same communication, the
 description might be very long. And he might use the oneway metrics
 with worst and the best value to give users an idea of the
 performance range of the service they are providing. But it is not
 clear enough and might not be accurate in a large multiparty
 communication scenario.

From the performance point of view, the multiparty communication
services not only require the absolute performance support but also
the relative performance. The relative performance means the
difference between absolute performance of all users. Directly using
the oneway metrics cannot present the relative performance
situation. However, if we use the variations of all users oneway
parameters, we can have new metrics to measure the difference of the
absolute performance and hence provide the threshold value of
relative performance that a multiparty service might demand. A very
good example of the high relative performance requirement is the
 online gaming. A very light worse delay will result in failure in
 the game. We have to use the new statistic metrics to define exactly
 how small the relative delay the online gaming requires. There are
 many other services, e.g. online biding, online stock market, etc.,
 need a rule to judge the relative performance requirement.
 Therefore, we can see the importance of new statistic metrics to feed
 this need.
+ online gaming. A very light difference in delay might result in
+ failure in the game. We have to use multicast specific statistic
+ metrics to define exactly how small the relative delay the online
+ gaming requires. There are many other services, e.g. online biding,
+ online stock market, etc., that require multicast metrics in order to
+ evaluate the network against their requirements. Therefore, we can
+ see the importance of new, multicast specific, statistic metrics to
+ feed this need.
 We might use some onetogroup statistic conceptions to present and
 report the group performance and relative performance to save the
+ We might also use some onetogroup statistic conceptions to present
+ and report the group performance and relative performance to save the
report transmission bandwidth. Statistics have been defined for One
way metrics in corresponding FRCs. They provide the foundation of
definition for performance statistics. For instance, there are
 definitions for minimum and maximum Oneway delay in [RFC2679] and
 Oneway delay mean in [ID.ietfippmspatialcomposition]. However,
 there is a dramatic difference between the statistics for onetoone
 communications and for onetomany communications. The former one
 only has statistics over the time dimension while the later one can
 have statistics over both time dimension and space dimention. This
 space dimension is introduced by the Matrix concept. For a Matrix M
 shown in the Fig. 2, each row is a set of Oneway singletons
 spreading over the space dimension and each colume is another set of
 Oneway singletons spreading over the time dimension.
+ definitions for minimum and maximum Oneway delay in [RFC2679].
+ However, there is a dramatic difference between the statistics for
+ onetoone communications and for onetomany communications. The
+ former one only has statistics over the time dimension while the
+ later one can have statistics over both time and space dimensions.
+ This space dimension is introduced by the Matrix concept as
+ illustrated in Figure 7. For a Matrix M each row is a set of Oneway
+ singletons spreading over the time dimension and each column is
+ another set of Oneway singletons spreading over the space dimension.
 (preamble)
 / \
  dT11, dT12,..., dT1N 
  dT21, dT22,..., dT2N 
  : 
  : 
  dTm1, dTm2,..., dTmN 
 \ /
+ Receivers
+ Space
+ ^
+ 1  / R1dT1 R1dT2 R1dT3 ... R3dTk \
+   
+ 2   R2dT1 R2dT2 R2dT3 ... R3dTk 
+   
+ 3   R3dT1 R3dT2 R3dT3 ... R3dTk 
+ .   
+ .   
+ .   
+ n  \ RndT1 RndT2 RndT3 ... RndTk /
+ +> time
+ T0
 Fig. 2 Matrix M (m*N)
+ Figure 7: Matrix M (n*m)
 In Matrix M, each element is a Oneway delay singleton. Each row is
 a delay vector contains the Oneway delays of the same packet
 observed at N points of interest. It implies the geographical factor
 of the performance within a group. Each colume is a set of Oneway
+ In Matrix M, each element is a Oneway delay singleton. Each column
+ is a delay vector contains the Oneway delays of the same packet
+ observed at M points of interest. It implies the geographical factor
+ of the performance within a group. Each row is a set of Oneway
delays observed during a sampling interval at one of the points of
interest. It presents the delay performance at a receiver over the
time dimension.
Therefore, one can either calculate statistics by rows over the space
 dimension or by columes over the time dimension. It's up to the
+ dimension or by columns over the time dimension. It's up to the
operators or service provides which dimension they are interested in.
For example, a TV broadcast service provider might want to know the
statistical performance of each user in a long term run to make sure
their services are acceptable and stable. While for an online gaming
service provider, he might be more interested to know if all users
 are served farely by calculating the statistics over the space
 dimension. This memo does not intent to recommend which of the
+ are served fairly by calculating the statistics over the space
+ dimension. This memo does not intend to recommend which of the
statistics are better than the other.
To save the report transmission bandwidth, each point of interest can
send statistics in a predefined time interval to the reference point
rather than sending every Oneway singleton it observed. As long as
 an appropriate time interval is decided, appropriate stantistics can
+ an appropriate time interval is decided, appropriate statistics can
represent the performance in a certain accurate scale. How to decide
the time interval and how to bootstrap all points of interest and the
reference point depend on applications. For instance, applications
with lower transmission rate can have the time interval longer and
ones with higher transmission rate can have the time interval
shorter. However, this is out of the scope of this memo.
Moreover, after knowing the statistics over the time dimension, one
might want to know how this statistics distributed over the space
dimension. For instance, a TV broadcast service provider had the
@@ 1125,169 +1125,769 @@
group of users during a sampling interval in terms of delay. It
needs twice calculation to have this statistic over both time and
space dimensions. We name this kind of statistics 2level statistics
to distinct with those 1level statistics calculated over either
space or time dimension. It can be easily prove that no matter over
which dimension a 2level statistic is calculated first, the results
are the same. I.e. one can calculate the 2level delay mean using
the Matrix M by having the 1level delay mean over the time dimension
first and then calculate the mean of the obtained vector to find out
the 2level delay mean. Or, he can do the 1level statistic
 calculation over the space dimention first and then have the 2level
+ calculation over the space dimension first and then have the 2level
delay mean. Both two results will be exactly the same. Therefore,
 when define a 2level statistic, it is no need to specify in which
+ when define a 2level statistic, there is no need to specify in which
procedure the calculation should follow.
 There are many statistics can be defined for the proposed oneto
 group metrics over either the space dimension or the time dimension
 or both. In this memo, we define onetogroup mean and onetogroup
 variation over the space dimension. These statistics are offered
 mostly to be illustrative of what could be done.
+ Comment: The above statement depends on whether the order of
+ operations has any affect on the outcome.
 Onetogroup mean are trying to measure the overall performance for a
 multicast group associated to one source. It is a reflection of the
 absolute performance of a multiparty communication service when we
 treat all receivers as one customer. It can also present the trend
 of the absolute performance of all receivers, i.e., it shows that
 most of the receivers in the multiparty communication service trend
 to receive an absolute performance close to the mean.
+ Many statistics can be defined for the proposed onetogroup metrics
+ over either the space dimension or the time dimension or both. This
+ memo treats the case where a stream of packets from the Source
+ results in a sample at each of the Receivers in the Group, and these
+ samples are each summarized with the usual statistics employed in
+ onetoone communication. New statistic definitions are presented,
+ which summarize the onetoone statistics over all the Receivers in
+ the Group.
 Onetogroup variation streams are trying to measure how the
 performance varies among all of the users in a multicast group
 associated to one source. The word "variation" in this memo is the
 population standard deviation. It reflects the relative
 performancesituation in a multiparty communication service, i.e., the
 level of the difference between the absolute performanceof each
 receivers.
+6.1. Discussion on the Impact of packet loss on statistics
 Using the onetogroup mean and onetogroup variation concepts, we
 can have a much clear understand on the performanceof a multiparty
 communication service in terms of its trend and range. There can be
 mean and variation stream definitions for each of the three oneto
 group metrics defined above. We only present the definition of Type
 PonetogroupOnewayDelaySpaceMean and TypePonetogroup One
 wayDelaySpaceVariation as examples in this memo.
+ The packet loss does have effects on oneway metrics and their
+ statistics. For example, the lost packet can result an infinite one
+ way delay. It is easy to handle the problem by simply ignoring the
+ infinite value in the metrics and in the calculation of the
+ corresponding statistics. However, the packet loss has so strong
+ impact on the statistics calculation for the onetogroup metrics
+ that it can not be solved by the same method used for oneway
+ metrics. This is due to the complex of building a Matrix, which is
+ needed for calculation of the statistics proposed in this memo.
5.4.1. TypePonetogroupOnewayDelaySpaceMean
+ The situation is that measurement results obtained by different end
+ users might have different packet loss pattern. For example, for
+ User1, packet A was observed lost. And for User2, packet A was
+ successfully received but packet B was lost. If the method to
+ overcome the packet loss for oneway metrics is applied, the two
+ singleton sets reported by User1 and User2 will be different in terms
+ of the transmitted packets. Moreover, if User1 and User2 have
+ different number of lost packets, the size of the results will be
+ different. Therefore, for the centralized calculation, the reference
+ point will not be able to use these two results to build up the group
+ Matrix and can not calculate the statistics. In an extreme
+ situation, no single packet arrives all users in the measurement and
+ the Matrix will be empty. One of the possible solutions is to
+ replace the infinite/undefined delay value by the average of the two
+ adjacent values. For example, if the result reported by user1 is {
+ R1dT1 R1dT2 R1dT3 ... R1dTK1 UNDEF R1dTK+1... R1DM } where "UNDEF"
+ is an undefined value, the reference point can replace it by R1dTK =
+ {(R1dTK1)+( R1dTK+1)}/2. Therefore, this result can be used to
+ build up the group Matrix with an estimated value R1dTK. There are
+ other possible solutions such as using the overall mean of the whole
+ result to replace the infinite/undefined value, and so on. It is out
+ of the scope of this memo.
 Given a TypePonetogroupOnewayDelayVector, the mean { dT1,
 dT2,...,dTN } for the packet from Src at time T to { Recv1,...,RecvN
 }.
+ For the distributed calculation, the reported statistics might have
+ different "weight" to present the group performance, which is
+ especially true for delay and jitter relevant metrics. For example,
+ User1 calculates the TypePFiniteOnewayDelayMean R1DM as shown
+ in Figure. 8 without any packet loss and User2 calculates the R2DM
+ with N2 packet loss. The R1DM and R2DM should not be treated with
+ equal weight because R2DM was calculated only based on 2 delay values
+ in the whole sample interval. One possible solution is to use a
+ weight factor to mark every statistic value sent by users and use
+ this factor for further statistic calculation.
 For example, suppose we take a delay vector and the results is:
+6.2. General Metric Parameters
 Delay_Vector = {dT1,...,dTN}
+ o Src, the IP address of a host
 Then the mean over space dimension would be:
+ o G, the Group IP address
 Delay_Space_Mean = DsM = sum{dT1,...,dTN}/N
+ o N, the number of Receivers (Recv1, Recv2, ... RecvN)
5.4.2. TypePonetogroupOnewayDelayVariationStream
+ o T, a time (start of test interval)
 Given a TypePonetogroupOnewayDelayVector, the variation {
 dT1, dT2,...,dTN } for the packet from Src at time T to {
 Recv1,...,RecvN }.
+ o Tf, a time (end of test interval)
 We still take the above Delay_Vector as an sample and the variation
 would be:
+ o K, the number of packets sent from the source during the test
+ interval
+ o J[n], the number of packets received at a particular Receiver, n,
+ where 1<=n<=N
 Delay_Variation_Stream = {SUM[(dT1DsM)^2,...,(dTN
 DsM)^2)}/N)^(1/2)
+ o lambda, a rate in reciprocal seconds (for Poisson Streams)
6. Extension from onetoone to onetomany measurement
+ o incT, the nominal duration of interpacket interval, first bit to
+ first bit (for Periodic Streams)
 The above onetogroup metrics were defined to compose measurement
 results of a group of users who receive the same data from one
 source. Moreover, this is one of efforts to introducing the oneto
 many concern to the IPPM working group with respect to the fact that
 all existing documents in the group are unicast oriented, which talk
 about only onetoone single "path" in measurements. This concept
 can be extended from the "path" to "path tree" to cover both oneto
 one and onetomany communications. Actually, the onetoone
 communications can be viewed as a special case of onetomany from
 the routing point of view. The onetomany communications build up a
 routing tree in the networks and onetoone can be viewed as a
 special simplified tree without branches but only the "trunk".
+ o T0, a time that MUST be selected at random from the interval [T,
+ T+I] to start generating packets and taking measurements (for
+ Periodic Streams)
 Therefore, the onetogroup metrics described in this memo can even
 be viewed as general metrics to measure the delay, jitter and packet
 loss in IP networks. When it applies to onetoone communications,
 the metrics will have N receivers while N equal to 1. And the
 statistic metrics for onetoone communications are exactly the one
 togroup metrics themselves when calculated using the methods given.
+ o TstampSrc, the wire time of the packet as measured at MP(Src) (the
+ Source Measurement Point)
7. Open issues
+ o TstampRecv, the wire time of the packet as measured at MP(Recv),
+ assigned to packets that arrive within a "reasonable" time
8. Security Considerations
+ o Tmax, a maximum waiting time for packets at the destination, set
+ sufficiently long to disambiguate packets with long delays from
+ packets that are discarded (lost), thus the distribution of delay
+ is not truncated
 Active measumrement: see security section in owd pl, jitter rfcs
 (editor notes: add references).
+ o dT, shorthand notation for a oneway delay singleton value
 passive measurement:
+ o L, shorthand notation for a oneway loss singleton value, either
+ zero or one, where L=1 indicates loss and L=0 indicates arrival at
+ the destination within TstampSrc + Tmax, may be indexed over n
+ Receivers
+
+ o DV, shorthand notation for a oneway delay variation singleton
+ value
+
+6.3. OnetoGroup oneway Delay Statistics
+
+ This section defines the overall oneway delay statistics for an
+ entire Group or receivers. For example, we can define the group mean
+ delay, as illustrated below. This is a metric designed to summarize
+ the entire Matrix.
+
+ Recv / Sample \ Stats Group Stat
+
+ 1 R1dT1 R1dT2 R1dT3 ... R1dTk R1DM \
+ 
+ 2 R2dT1 R2dT2 R2dT3 ... R2dTk R2DM 
+ 
+ 3 R3dT1 R3dT2 R3dT3 ... R3dTk R2DM > GMD
+ . 
+ . 
+ . 
+ n RndT1 RndT2 RndT3 ... RndTk RnDM /
+
+ Figure 8: OnetoGroupGroup Mean Delay
+
+ where:
+
+ R1dT1 is the TypePFiniteOnewayDelay singleton evaluated at
+ Receiver 1 for packet 1.
+
+ R1DM is the TypePFiniteOnewayDelayMean evaluated at Receiver 1
+ for the sample of packets (1,...K).
+
+ GMD is the mean of the sample means over all Receivers (1, ...N).
+
+6.3.1. Definition and Metric Units
+
+ Using the parameters above, we obtain the value of TypePOneway
+ Delay singleton for all packets sent during the test interval at each
+ Receiver (Destination), as per [RFC2679]. For each packet that
+ arrives within Tmax of its sending time, TstampSrc, the oneway delay
+ singleton (dT) will be a finite value in units of seconds.
+ Otherwise, the value of the singleton is Undefined.
+
+ For each packet [i] that has a finite Oneway Delay at Receiver n (in
+ other words, excluding packets which have undefined oneway delay):
+
+ TypePFiniteOnewayDelayReceivern[i] =
+
+ = TstampRecv[i]  TstampSrc[i]
+
+ The units of Finite oneway delay are seconds, with sufficient
+ resolution to convey 3 significant digits.
+
+6.3.2. Sample Mean Statistic
+
+ This section defines the Sample Mean at each of N Receivers.
+
+ TypePFiniteOnewayDelayMeanReceivern = RnDM =
+ J[n]
+ 
+ 1 \
+  * > TypePFiniteOnewayDelayReceivern[i]
+ J[n] /
+ 
+ i = 1
+
+ Figure 9: TypePFiniteOnewayDelayMeanReceivern
+
+ where all packets i= 1 through J[n] have finite singleton delays.
+
+6.3.3. OnetoGroup Mean Delay Statistic
+
+ This section defines the Mean Oneway Delay calculated over the
+ entire Group (or Matrix).
+
+ TypePOnetoGroupMeanDelay = GMD =
+ N
+ 
+ 1 \
+  * > RnDM
+ N /
+ 
+ n = 1
+
+ Figure 10: TypePOnetoGroupMeanDelay
+
+ Note that the Group Mean Delay can also be calculated by summing the
+ Finite oneway Delay singletons in the Matrix, and dividing by the
+ number of Finite Oneway Delay singletons.
+
+6.3.4. OnetoGroup Range of Mean Delays
+
+ This section defines a metric for the range of mean delays over all N
+ receivers in the Group, (R1DM, R2DM,...RnDM).
+
+ TypePOnetoGroupRangeMeanDelay = GRMD = max(RnDM)  min(RnDM)
+
+6.3.5. OnetoGroup Maximum of Mean Delays
+
+ This section defines a metrics for the maximum of mean delays over
+ all N receivers in the Group, (R1DM, R2DM,...RnDM).
+
+ TypePOnetoGroupMaxMeanDelay = GMMD = max(RnDM)
+
+6.4. OnetoGroup oneway Loss Statistics
+
+ This section defines the overall 1way loss statistics for an entire
+ Group. For example, we can define the group loss ratio, as
+ illustrated below. This is a metric designed to summarize the entire
+ Matrix.
+
+ Recv / Sample \ Stats Group Stat
+
+ 1 R1L1 R1L2 R1L3 ... R1Lk R1LR \
+ 
+ 2 R2L1 R2L2 R2L3 ... R2Lk R2LR 
+ 
+ 3 R3L1 R3L2 R3L3 ... R3Lk R3LR > GLR
+ . 
+ . 
+ . 
+ n RnL1 RnL2 RnL3 ... RnLk RnLR /
+
+ Figure 11: OnetoGroup Loss Ratio
+
+ where:
+
+ R1L1 is the TypePOnewayLoss singleton (L) evaluated at Receiver 1
+ for packet 1.
+
+ R1LR is the TypePOnewayLossRatio evaluated at Receiver 1 for the
+ sample of packets (1,...K).
+
+ GLR is the loss ratio over all Receivers (1, ..., N).
+
+6.4.1. OnetoGroup Loss Ratio
+
+ The overall Group loss ratio id defined as
+
+ TypePOnetoGroupLossRatio =
+ K,N
+ 
+ 1 \
+ =  * > L(k,n)
+ K*N /
+ 
+ k,n = 1
+
+ Figure 12
+
+ ALL Loss ratios are expressed in units of packets lost to total
+ packets sent.
+
+6.4.2. OnetoGroup Loss Ratio Range
+
+ Given a Matrix of loss singletons as illustrated above, determine the
+ TypePOnewayPacketLossAverage for the sample at each receiver,
+ according to the definitions and method of [RFC2680]. The TypeP
+ OnewayPacketLossAverage, RnLR for receiver n, and the TypePOne
+ wayLossRatio illustrated above are equivalent metrics. In terms of
+ the parameters used here, these metrics definitions can be expressed
+ as
+
+ TypePOnewayLossRatioReceivern = RnLR =
+ K
+ 
+ 1 \
+  * > RnLk
+ K /
+ 
+ k = 1
+
+ Figure 13: TypePOnewayLossRatioReceivern
+
+ The OnetoGroup Loss Ratio Range is defined as
+
+ TypePOnetoGroupLossRatioRange = max(RnLR)  min(RnLR)
+
+ It is most effective to indicate the range by giving both the max and
+ minimum loss ratios for the Group, rather than only reporting the
+ difference between them.
+
+6.4.3. Comparative Loss Ratio
+
+ Usually, the number of packets sent is used in the denominator of
+ packet loss ratio metrics. For the comparative metrics defined here,
+ the denominator is the maximum number of packets received at any
+ receiver for the sample and test interval of interest.
+
+ The Comparative Loss Ratio is defined as
+
+ TypePCompLossRatioReceivern = RnCLR =
+ K
+ 
+ \
+ > Ln(k)
+ /
+ 
+ k=1
+ = 
+ / K \
+   
+  \ 
+ K  Min  > Ln(k) 
+  / 
+   
+ \ k=1 / N
+
+ Figure 14: TypePCompLossRatioReceivern
+
+6.5. OnetoGroup oneway Delay Variation Statistics
+
+ There is are two delay variation (DV) statistics to summarize the
+ performance over the Group: the maximum DV over all receivers and the
+ range of DV over all receivers.
+
+ The detailed definitions are T0 BE PROVIDED.
+
+7. Measurement Methods: Scaleability and Reporting
+
+ Virtually all the guidance on measurement processes supplied by the
+ earlier IPPM RFCs (such as [RFC2679] and [RFC2680]) for onetoone
+ scenarios is applicable here in the spatial and multiparty
+ measurement scenario. The main difference is that the spatial and
+ multiparty configurations require multiple measurement points where a
+ stream of singletons will be collected. The amount of information
+ requiring storage grows with both the number of metrics and the
+ number of measurement points, so the scale of the measurement
+ architecture multiplies the number of singleton results that must be
+ collected and processed.
+
+ It is possible that the architecture for results collection involves
+ a single aggregation point with connectivity to all the measurement
+ points. In this case, the number of measurement points determines
+ both storage capacity and packet transfer capacity of the host acting
+ as the aggregation point. However, both the storage and transfer
+ capacity can be reduced if the measurement points are capable of
+ computing the summary statistics that describe each measurement
+ interval. This is consistent with many operational monitoring
+ architectures today, where even the individual singletons may not be
+ stored at each measurement point.
+
+ In recognition of the likely need to minimize form of the results for
+ storage and communication, the Group metrics above have been
+ constructed to allow some computations on a perReceiver basis. This
+ means that each Receiver's statistics would normally have an equal
+ weight with all other Receivers in the Group (regardless of the
+ number of packets received).
+
+7.1. Computation methods
+
+ The scalability issue can be raised when there are thousands of
+ points of interest in a group who are trying to send back the
+ measurement results to the reference point for further processing and
+ analysis. The points of interest can send either the whole measured
+ sample or only the calculated statistics. The former one is a
+ centralized statistic calculation method and the latter one is a
+ distributed statistic calculation method. The sample should include
+ all metrics parameters, the values and the corresponding sequence
+ numbers. The transmission of the whole sample can cost much more
+ bandwidth than the transmission of the statistics that should include
+ all statistic parameters specified by policies and the additional
+ information about the whole sample, such as the size of the sample,
+ the group address, the address of the point of interest, the ID of
+ the sample session, and so on. Apparently, the centralized
+ calculation method can require much more bandwidth than the
+ distributed calculation method when the sample size is big. This is
+ especially true when the measurement has huge number of the points of
+ interest. It can lead to a scalability issue at the reference point
+ by over load the network resources. The distributed calculation
+ method can save much more bandwidth and release the pressure of the
+ scalability issue at the reference point side. However, it can
+ result in the lack of information because not all measured singletons
+ are obtained for building up the group matrix. The performance over
+ time can be hidden from the analysis. For example, the loss pattern
+ can be missed by simply accepting the loss ratio as well as the delay
+ pattern. This tradeoff between the bandwidth consuming and the
+ information acquiring has to be taken into account when design the
+ measurement campaign to optimize the measurement results delivery.
+ The possible solution could be to transit the statistic parameters to
+ the reference point first to obtain the general information of the
+ group performance. If the detail results are required, the reference
+ point should send the requests to the points of interest, which could
+ be particular ones or the whole group. This procedure can happen in
+ the off peak time and can be well scheduled to avoid delivery of too
+ many points of interest at the same time. Compression techniques can
+ also be used to minimize the bandwidth required by the transmission.
+ This could be a measurement protocol to report the measurement
+ results. It is out of the scope of this memo.
+
+7.2. Measurement
+
+ To prevent any biais in the result, the configuration of a oneto
+ many measure must take in consideration that implicitly more packets
+ will to be routed than send and selects a test packets rate that will
+ not impact the network performance.
+
+7.3. effect of Time and Space Aggregation Order on Group Stats
+
+ This section presents the impact of the aggregation order on the
+ scalability of the reporting and of the the computation. It makes
+ the hypothesis that receivers are managed remotly and not colocated.
+
+ 2 methods are available to compute group statistics:
+
+ Figure 8and (Figure 11) illustrate the method method choosen: the
+ onetoone statistic is computed per interval of time before the
+ computation of the mean over the group of receivers [method1];
+
+ Figure 15 presents the second one, metric is computed over space
+ and then over time [method2].
+
+ They differ only by the order of the time and of the space
+ aggregation. View as a matrix this order is neutral as it does not
+ impact the result, but the impact on a measurement deployement is
+ critical.
+
+ Recv
+
+ 1 R1S1 R1S1 R1S1 ... R1Sk \
+ 
+ 2 R2S1 R2S2 R2S3 ... R2Sk 
+ 
+ 3 R3S1 R3S2 R3S3 ... R3Sk > sample over space
+ . 
+ . 
+ . 
+ n RnS1 RnS2 RnS3 ... RnSk /
+
+ S1M S2M S3M ... SnM Stats over space
+
+ \ /
+ \/
+ Group Stat over space and time
+
+ Figure 15: Impact of space aggregation on Group Stat
+
+ In both cases the volume of data to report is proportional to the
+ number of probes. But there is a major difference between these 2
+ methods:
+
+ method2: In space and time aggregation mode the volume of data to
+ collect is proportionnal to the number of test packets received;
+ Each received packet RiSi triggers out a block of data that must
+ be reported to a common place for computing the stat over space;
+
+ method1: In time and space aggregation mode the volume of data to
+ collect is proportionnal to the period of aggregation, so it does
+ not depend on the number of packet received;
+
+ Method 2 property has severe drawbacks in terms of security and
+ dimensionning:
+
+ The increasing of the rate of the test packets may result in a
+ sort of DoS toward the computation points;
+
+ The dimensioning of a measurement system is quite impossible to
+ validate.
+
+ The time agregation interval provides the reporting side with a
+ control of various collecting aspects such as bandwidth and
+ computation and storage capacities. So this draft defines metrics
+ based on method 1.
+
+ Note: In some specific cases one may need sample of singletons over
+ space. To adress this need it is suggested firstly to limit the
+ number of test and the number of test packets per seconds. Then
+ reducing the size of the sample over time to one packet give sample
+ of singleton over space..
+
+7.4. effect of Time and Space Aggregation Order on Spatial Stats
+
+ TBD
+
+8. Open issues
+
+9. Security Considerations
+
+ Active measurement: (TODO: security considerations of owd pl, jitter
+ rfcs applies (editor notes: add references).
+
+9.1. passive measurement
The generation of packets which match systematically the hash
function may lead to a DoS attack toward the collector.
 The generation of packets with spoofing adresses may corrupt the
+ The generation of packets with spoofing addresses may corrupt the
results without any possibility to detect the spoofing.
 onetogroup metrics require collection of singletons which may
 overload the network the measurement controller is attach to.
+9.2. onetogroup metric
9. Acknowledgments
+ The configuration of a measure must take in consideration that
+ implicitly more packets will to be routed than send and selects a
+ test packets rate accordingly.
+
+ Collecting statistics from a huge number of probes may overload any
+ combination of the network the measurement controller is attach to,
+ measurement controller network interfaces and measurement controller
+ computation capacities.
+
+ onetogroup metrics:
+
+10. Acknowledgments
Lei would like to acknowledge Zhili Sun from CCSR, University of
Surrey, for his instruction and helpful comments on this work.
10. IANA Considerations
+11. IANA Considerations
 Metrics defined in this memo will be registered in the IANA IPPM
 METRICS REGISTRY as described in initial version of the registry
 [RFC4148].
+ Metrics defined in this memo Metrics defined in this memo are
+ designed to be registered in the IANA IPPM METRICS REGISTRY as
+ described in initial version of the registry [RFC4148] :
11. References
+ IANA is asked to register the following metrics in the IANAIPPM
+ METRICSREGISTRYMIB :
11.1. Normative References
+ SpatialOnewayDelayVector OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePSpatialOnewayDelayVector"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 4.1."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ subpathOnewayDelayStream OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePsubpathOnewayDelayStream"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 4.2."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ SpatialOnewayPacketLossVector OBJECTIDENTITY
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePSpatialOnewayPacketLossVector"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 4.3."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ SpatialOnewayJitterVector OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePSpatialOnewayJitterVector"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 4.4."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ onetogroupOnewayDelayVector OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePonetogroupOnewayDelayVector"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 5.1."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+ onetogroupOnewayPacketLossVector OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePonetogroupOnewayPacketLossVector"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 5.2."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ onetogroupOnewayJitterVector OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePonetogroupOnewayJitterVector"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 5.3."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ OnetoGroupMeanDelay OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePOnetoGroupMeanDelay"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 6.3.3."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ OnetoGroupRangeMeanDelay OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePOnetoGroupRangeMeanDelay"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 6.3.4."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ OnetoGroupMaxMeanDelay OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePOnetoGroupMaxMeanDelay"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 6.3.5."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ OnetoGroupLossRatio OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePOnetoGroupLossRatio"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 6.4.1."
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ 
+
+ OnetoGroupLossRatioRange OBJECTIDENTITY
+
+ STATUS current
+
+ DESCRIPTION
+
+ "TypePOnetoGroupLossRatioRange"
+
+ REFERENCE
+
+ "Reference "RFCyyyy, section 6.4.2."
+
+  RFC Ed.: replace yyyy with actual RFC number & remove this
+ note
+
+ := { ianaIppmMetrics nn }  IANA assigns nn
+
+ 
+
+12. References
+
+12.1. Normative References
[RFC2330] Paxson, V., Almes, G., Mahdavi, J., and M. Mathis,
"Framework for IP Performance Metrics", RFC 2330,
May 1998.
[RFC2679] Almes, G., Kalidindi, S., and M. Zekauskas, "A Oneway
Delay Metric for IPPM", RFC 2679, September 1999.
[RFC2680] Almes, G., Kalidindi, S., and M. Zekauskas, "A Oneway
Packet Loss Metric for IPPM", RFC 2680, September 1999.
[RFC3393] Demichelis, C. and P. Chimento, "IP Packet Delay Variation
Metric for IP Performance Metrics (IPPM)", RFC 3393,
November 2002.
[RFC4148] Stephan, E., "IP Performance Metrics (IPPM) Metrics
Registry", BCP 108, RFC 4148, August 2005.
11.2. Informative References

 [ID.boschiipfixreducingredundancy]
 Boschi, E., "Reducing redundancy in IPFIX and PSAMP
 reports", draftboschiipfixreducingredundancy02 (work
 in progress), June 2006.

 [ID.ietfippmspatialcomposition]
 Morton, A. and E. Stephan, "Spatial Composition of
 Metrics", draftietfippmspatialcomposition01 (work in
 progress), June 2006.

 [ID.quittekipfixmiddlebox]
 Quittek, J., "Guidelines for IPFIX Implementations on
 Middleboxes", draftquittekipfixmiddlebox00 (work in
 progress), February 2004.
+12.2. Informative References
[RFC2678] Mahdavi, J. and V. Paxson, "IPPM Metrics for Measuring
Connectivity", RFC 2678, September 1999.
[RFC2681] Almes, G., Kalidindi, S., and M. Zekauskas, "A Roundtrip
Delay Metric for IPPM", RFC 2681, September 1999.
[RFC3148] Mathis, M. and M. Allman, "A Framework for Defining
Empirical Bulk Transfer Capacity Metrics", RFC 3148,
July 2001.
@@ 1296,60 +1896,67 @@
Metrics", RFC 3357, August 2002.
[RFC3432] Raisanen, V., Grotefeld, G., and A. Morton, "Network
performance measurement with periodic streams", RFC 3432,
November 2002.
[RFC3763] Shalunov, S. and B. Teitelbaum, "Oneway Active
Measurement Protocol (OWAMP) Requirements", RFC 3763,
April 2004.
+ [RFC4656] Shalunov, S., Teitelbaum, B., Karp, A., Boote, J., and M.
+ Zekauskas, "A Oneway Active Measurement Protocol
+ (OWAMP)", RFC 4656, September 2006.
+
+ [RFC4737] Morton, A., Ciavattone, L., Ramachandran, G., Shalunov,
+ S., and J. Perser, "Packet Reordering Metrics", RFC 4737,
+ November 2006.
+
Authors' Addresses
Stephan Emile
France Telecom Division R&D
2 avenue Pierre Marzin
Lannion, F22307
Fax: +33 2 96 05 18 52
 Email: emile.stephan@orangeft.com

+ Email: emile.stephan@orangeftgroup.com
Lei Liang
CCSR, University of Surrey
Guildford
Surrey, GU2 7XH
Fax: +44 1483 683641
Email: L.Liang@surrey.ac.uk
Al Morton
200 Laurel Ave. South
Middletown, NJ 07748
USA
Phone: +1 732 420 1571
Email: acmorton@att.com
Full Copyright Statement
 Copyright (C) The Internet Society (2006).
+ Copyright (C) The IETF Trust (2007).
This document is subject to the rights, licenses and restrictions
contained in BCP 78, and except as set forth therein, the authors
retain all their rights.
This document and the information contained herein are provided on an
"AS IS" basis and THE CONTRIBUTOR, THE ORGANIZATION HE/SHE REPRESENTS
 OR IS SPONSORED BY (IF ANY), THE INTERNET SOCIETY AND THE INTERNET
 ENGINEERING TASK FORCE DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED,
 INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE
 INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED
+ OR IS SPONSORED BY (IF ANY), THE INTERNET SOCIETY, THE IETF TRUST AND
+ THE INTERNET ENGINEERING TASK FORCE DISCLAIM ALL WARRANTIES, EXPRESS
+ OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF
+ THE INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED
WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
Intellectual Property
The IETF takes no position regarding the validity or scope of any
Intellectual Property Rights or other rights that might be claimed to
pertain to the implementation or use of the technology described in
this document or the extent to which any license under such rights
might or might not be available; nor does it represent that it has
made any independent effort to identify any such rights. Information