Network Working Group E. Stephan
InternetDraft France Telecom
Intended status: Informational L. Liang
Expires: September 2, 2007 University of Surrey
A. Morton
AT&T Labs
March 1, 2007
IP Performance Metrics (IPPM) for spatial and multicast
draftietfippmmultimetrics03
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Copyright Notice
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
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users in multiparty communications.
Table of Contents
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 . 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
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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
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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 [RFC2330];
o A Oneway Active Measurement Protocol Requirements [RFC3763];
o A Oneway Active Measurement Protocol (OWAMP) [RFC4656];
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 [RFC2678];
o The Oneway Delay Metric for IPPM [RFC2679];
o The Oneway Packet Loss Metric for IPPM [RFC2680];
o The Roundtrip Delay Metric for IPPM [RFC2681];
o A Framework for Defining Empirical Bulk Transfer Capacity Metrics
[RFC3148];
o Oneway Loss Pattern Sample Metrics [RFC3357];
o IP Packet Delay Variation Metric for IPPM [RFC3393];
o Network performance measurement for periodic streams [RFC3432];
o Packet Reordering Metric for IPPM [RFC4737][Work in progress];
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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
be introduced to divide an endtoend TypePOnewayPacketLoss
in a spatial sequence of packet loss.
o Using the TypePSpatialOnewayDelayVector metric, a 'sample',
called TypePSpatialOnewayJitterVector, will be introduced to
divide an endtoend TypePOnewayipdv in a spatial sequence of
jitter.
o Using the TypePSpatialOnewayDelayVector metric, a 'sample',
called TypePsubpathOnewayDelayStream, will be introduced to
define the onewaydelay between a pair of host of the path. This
metric is similar to TypePOnewayDelayStream.
o Using TypePsubpathOnewayDelayStream, a 'sample' TypeP
PassiveOnewayDelayStream will be introduced to define passive
metrics. These metrics are designed for pure passive measurement
methodology as introduced by PSAMP WG.
Then it defines onetogroup metrics.
o Using one test packet sent from one sender to a group of
receivers, a 'sample', called TypePonetogroupOnewayDelay
Vector, will be introduced to define the list of TypePoneway
delay between this sender and the group of receivers.
o Using one test packet sent from one sender to a group of
receivers, a 'sample', called TypePonetogroupOnewayPacket
LossVector, will be introduced to define the list of TypePOne
wayPacketLoss between this sender and the group of receivers
o Using one test packet sent from one sender to a group of
receivers, a 'sample', called TypePonetogroupOnewayJitter
Vector, will be introduced to define the list of TypePOneway
ipdv between this sender and the group of receivers
o Then a discussion section presents the set of statistics that may
be computed on the top of these metrics to present the QoS in a
view of a group of users as well as the requirements of relative
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QoS on multiparty communications.
2. Terminology
2.1. Multiparty metric
A metric is said to be multiparty if the definition involved more
than two sources or destinations in the measurements. All multiparty
metrics define a set of hosts called "points of interest", where one
host is the source and other hosts are the measurement collection
points. For example, if the set of points of interest is < ha, hb,
hc, ..., hn >, where ha is the source and < hb, hc, ..., hn > are the
destinations, then measurements may be conducted between < ha, hb>, <
ha, hc>, ..., .
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 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
Points of interest of Onetogroup metrics are the set of host
destinations receiving packets from the source (in addition to the
source itself).
2.6. Reference point
The centre/server in the onetogroup measurement that is controlled
by network operators can be a very good reference point where
measurement data can be collected for further processing although the
actual measurements have to be carried out at all points of interest.
I.e., the measurement points will be all clients/receivers while the
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reference point acts as source for the onetogroup metric. Thus, we
can define the reference point as the host while the statistic
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 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 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 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 corresponds to a sample.
The relation among Singleton, Vector and Matrix can be shown in the
following Figure 1.
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onetogroup Singleton
/ Sample
Src Recv ..............................
.................... 1 R1dT1 R1dT2 R1dT3 R1dT4
`:=.._
T `._ ``..__
`. `... 2 R2dT1 R2dT2 R2dT3 R2dT4
`.
`.
`.... N R3dT1 R3dT2 R3dT3 R3dT4
Vector Matrix
(space) (time)
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 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. Spatial measure give typically the individual performance
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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 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.
A group of metrics are proposed in this stage named onetogroup
performance metrics based on the unicast metrics defined in IPPM WG.
Onetogroup metrics are trying to composite oneway metrics from one
source to a group of destinations to make up new metrics. The
compositions are necessary for judging the network performance of
multiparty communications and can also be used to describe the
difference of the QoS served among a group of users.
Onetogroup performance metrics are needed for several reasons:
o For designing and engineering multicast trees and MPLS pointto
multipoint LSP;
o For evaluating and controlling of the quality of the multicast
services;
o For controlling the performance of the inter domain multicast
services;
o For presenting and evaluating the relative QoS requirements for
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.
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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
point that is acting as a receiver while all of clients/receivers
defined for onetogroup measurement act as sources in this case.
For the grouptogroup connection topology, we can hardly define the
reference point and, therefore, have difficulty to define the
measurement points. However, we can always avoid this confusion by
treating the connections as onetogroup or grouptoone in our
measurements without consideration on how the real communication will
be carried out. For example, if one group of hosts < ha, hb, hc,
..., hn > are acting as sources to send data to another group of
hosts < Ha, Hb, Hc, ..., Hm >, we can always decompose them into n
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 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
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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.
Spatial onewaydelay measurement SHOULD be respectful of them,
especially those related to methodology, clock, uncertainties and
reporting.
Following we adapt some of them and introduce points specific to
spatial measurement.
4.1.1. Metric Name
TypePSpatialOnewayDelayVector
4.1.2. Metric Parameters
+ Src*, the IP address of the sender.
+ Dst*, the IP address of the receiver.
+ i, An integer which ordered the hosts in the path.
+ Hi, exchange points of the path digest.
+ T*, a time, the sending (or initial observation) time for
a measured packet.
+ dT* a delay, the oneway delay for a measured packet.
+ dT1,..., dTn a list of delay.
+ P*, the specification of the packet type.
+ , a path digest.
4.1.3. Metric Units
A sequence of times.
4.1.4. Definition
Given a TypeP packet sent by the sender Src at wiretime (first bit)
T to the receiver Dst in the path . Given the
sequence of values such that dT is the
TypePOnewayDelay from Src to Dst and such that for each Hi of the
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path, T+dTi is either a real number corresponding to the wiretime
the packet passes (last bit received) Hi, or undefined if the packet
never passes Hi.
TypePSpatialOnewayDelayVector metric is defined for the path
as the sequence of values
.
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. 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.
4.1.8. Methodologies
Section 3.6 of [RFC2679] gives methodologies for endtoend oneway
delay measurements. Most of them apply to each points interest Hi
and are relevant to this section.
Generally, for a given TypeP, in a given Hi, the methodology would
proceed as follows:
o At each Hi, prepare to capture the packet sent a time T, take a
timestamp Ti', determine the internal delay correction dTi',
extract the timestamp T from the packet, then compute the oneway
delay from Src to Hi: dTi = Ti'  dTi'  T. The oneway delay is
undefined (infinite) if the packet is not detected after the 'loss
threshold' duration;
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o Gather the set of dTi of each Hi and order them according to the
path to build the TypePSpatialOnewayDelayVector metric
over the path .
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 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
stream defined in [RFC2679] and to the metric TypePOnewayDelay
PeriodicStream defined in [RFC3432].
Nevertheless its definition differs because it is based of the
division of endtoend Oneway delay using the metric TypePSpatial
OnewayDelayVector defined above.
It aims is to define a sample of OnewayDelay between a pair of
hosts of a path usable by active and passive measurements.
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.
Subpath onewaydelay measurement SHOULD be respectful of them,
especially those related to methodology, clock, uncertainties and
reporting.
4.2.1. Metric Name
TypePsubpathOnewayDelayStream
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4.2.2. Metric Parameters
+ Src*, the IP address of the sender.
+ Dst*, the IP address of the receiver.
+ i, An integer which orders exchange points in the path.
+ k, An integer which orders the packets sent.
+ , a path digest.
+ Ha, a host of the path digest different from Dst and Hb;
+ Hb, a host of the path digest different from Src and Ha.
Hb order in the path must greater that Ha;
+ Hi, exchange points of the path digest.
+ dT1,..., dTn a list of delay.
+ P*, the specification of the packet type.
4.2.3. Metric Units
A sequence of pairs .
T is one of time of the sequence T1...Tn;
dt is a delay.
4.2.4. Definition
Given 2 hosts Ha and Hb of the path , given
a flow of packets of TypeP sent from Src to Dst at the times T1,
T2... Tn. At each of these times, we obtain a TypePSpatialOne
wayDelayVector . We define the
value of the sample TypePsubpathOnewayDelayStream as the
sequence made up of the couples . dTk.a is the
delay between Src and Ha. dTk.b is the delay between Src and Hb.
'dTk.b  dTk.a' is the oneway delay experienced by the packet sent
at the time Tk by Src when going from Ha to Hb.
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4.2.5. Discussion
Following are specific issues which may occur:
o When a is Src is the measure of the first hop.
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 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. 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.
4.2.6. Interference with other packet
4.2.7. 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.
4.2.8. Methodologies
Both active and passive method should discussed.
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4.2.9. Reporting the metric
Section 3.6 of [RFC2679] indicates the items to report.
4.2.10. Path
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, 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
+ Src*, the IP address of the sender.
+ Dst*, the IP address of the receiver.
+ i, An integer which ordered the hosts in the path.
+ Hi, exchange points of the path digest.
+ 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.
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4.3.3. Metric Units
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 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;
4.3.6. Reporting
Section in progress.
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, uncertainties and
reporting.
Following we adapt some of them and introduce points specific to
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spatial measurement.
4.4.1. Metric Name
TypePSpatialOnewayJitterVector
4.4.2. Metric Parameters
+ Src*, the IP address of the sender.
+ Dst*, the IP address of the receiver.
+ i, An integer which ordered the hosts in the path.
+ Hi, exchange points of the path digest.
+ T1*, the time the first packet was sent.
+ T2*, the time the second packet was sent.
+ P, the specification of the packet type.
+ P1, the first packet sent at time T1.
+ P2, the second packet sent at time T2.
+ , a path digest.
+ ,
the TypePSpatialOnewayDelayVector for packet sent at
time T1;
+ ,
the TypePSpatialOnewayDelayVector for packet sent at
time T2;
+ L*, a packet length in bits. The packets of a Type P
packet stream from which the
TypePSpatialOnewayDelayVector metric is taken MUST
all be of the same length.
4.4.3. Metric Units
A sequence of times.
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4.4.4. Definition
Given the TypeP packet having the size L and sent by the sender Src
at wiretime (first bit) T1 to the receiver Dst in the path .
Given the TypeP packet having the size L and sent by the sender Src
at wiretime (first bit) T2 to the receiver Dst in the same path.
Given the TypePSpatialOnewayDelayVector of the packet P1.
Given the TypePSpatialOnewayDelayVector of the packet P2.
TypePSpatialOnewayJitterVector metric is defined as the
sequence of values Such that for each Hi of the path ,
dT2.idT1.i is either a real number if the packets P1 and P2 passes
Hi at wiretime (last bit) dT1.i, respectively dT2.i, or undefined if
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.
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
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
send. So It is not possible to measure the delay between Src and Hi
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in the same manner it is not possible to measure the delay betwwen Hi
and Dst.
4.5.1.2. Passive Packet loss
The packet is not a test packet, so it does not include a sequence
number.
Packet lost measurement doe not require time synchronization and
require only one point of observation. Nevertheless it requires the
point of interest Hi to be expecting the packet. Practically Hi may
not detect a lost of packet that occurs between Src and Hi.
A point of interest Hi ignores the time the packet is send because
the packet does not carry the time it was injected in the network.
So a probe Hi can not compute dTi.
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 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 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
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4.6. Discussion on spatial statistics
Do we define min, max, avg of spatial metrics ?
having the maximum loss metric value could be interesting. Say,
the segment between router A and B always contributes loss metric
value of "1" means it could be the potential problem segment.
Uploading dTi of each Hi consume a lot of bandwidth. Computing
statistics (min, max and avg) of dTi locally in each Hi reduce the
bandwidth consumption.
5. Onetogroup metrics definitions
5.1. A Definition for onetogroup Oneway Delay
5.1.1. Metric Name
TypePonetogroupOnewayDelayVector
5.1.2. Metric Parameters
o Src, the IP address of a host acting as the source.
o Recv1,..., RecvN, the IP addresses of the N hosts acting as
receivers.
o T, a time.
o dT1,...,dTn a list of time.
o P, the specification of the packet type.
o Gr, the multicast group address (optional). The parameter Gr is
the multicast group address if the measured packets are
transmitted by multicast. This parameter is to identify the
measured traffic from other unicast and multicast traffic. It is
set to be optional in the metric to avoid losing any generality,
i.e. to make the metric also applicable to unicast measurement
where there is only one receivers.
5.1.3. Metric Units
The value of a TypePonetogroupOnewayDelayVector is a set of
singletons metrics TypePOnewayDelay [RFC2679].
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5.1.4. Definition
Given a Type P packet sent by the source Src at Time T, given the N
hosts { Recv1,...,RecvN } which receive the packet at the time {
T+dT1,...,T+dTn }, a TypePonetogroupOnewayDelayVector is
defined as the set of the TypePOnewayDelay singleton between Src
and each receiver with value of { dT1, dT2,...,dTn }.
5.2. A Definition for onetogroup Oneway Packet Loss
5.2.1. Metric Name
TypePonetogroupOnewayPacketLossVector
5.2.2. Metric Parameters
o Src, the IP address of a host acting as the source.
o Recv1,..., RecvN, the IP addresses of the N hosts acting as
receivers.
o T, a time.
o T1,...,Tn a list of time.
o P, the specification of the packet type.
o Gr, the multicast group address (optional).
5.2.3. Metric Units
The value of a TypePonetogroupOnewayPacketLossVector is a
set of singletons metrics TypePOnewayPacketLoss [RFC2680].
5.2.4. Definition
Given a Type P packet sent by the source Src at T and the N hosts,
Recv1,...,RecvN, which should receive the packet at T1,...,Tn, a
TypePonetogroupOnewayPacketLossVector is defined as a set of
the TypePOnewayPacketLoss singleton between Src and each of the
receivers {,,..., }.
5.3. A Definition for onetogroup Oneway Jitter
5.3.1. Metric Name
TypePonetogroupOnewayJitterVector
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5.3.2. Metric Parameters
+ Src, the IP address of a host acting as the source.
+ Recv1,..., RecvN, the IP addresses of the N hosts acting as
receivers.
+ T1, a time.
+ T2, a time.
+ ddT1,...,ddTn, a list of time.
+ P, the specification of the packet type.
+ F, a selection function defining unambiguously the two
packets from the stream selected for the metric.
+ Gr, the multicast group address (optional)
5.3.3. Metric Units
The value of a TypePonetogroupOnewayJitterVector is a set of
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 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}.
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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.
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 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 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].
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.
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Receivers
Space
^
1  / R1dT1 R1dT2 R1dT3 ... R3dTk \
  
2   R2dT1 R2dT2 R2dT3 ... R3dTk 
  
3   R3dT1 R3dT2 R3dT3 ... R3dTk 
.   
.   
.   
n  \ RndT1 RndT2 RndT3 ... RndTk /
+> time
T0
Figure 7: Matrix M (n*m)
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 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 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 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
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might want to know how this statistics distributed over the space
dimension. For instance, a TV broadcast service provider had the
performance Matrix M and calculated the Oneway delay mean over the
time dimension to obtain a delay Vector as {V1,V2,..., VN}. He then
calculated the mean of all the elements in the Vector to see what
level of delay he has served to all N users. This new delay mean
gives information on how good the service has been delivered to a
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 dimension first and then have the 2level
delay mean. Both two results will be exactly the same. Therefore,
when define a 2level statistic, there is no need to specify in which
procedure the calculation should follow.
Comment: The above statement depends on whether the order of
operations has any affect on the outcome.
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.
6.1. Discussion on the Impact of packet loss on statistics
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.
The situation is that measurement results obtained by different end
users might have different packet loss pattern. For example, for
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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.
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.
6.2. General Metric Parameters
o Src, the IP address of a host
o G, the Group IP address
o N, the number of Receivers (Recv1, Recv2, ... RecvN)
o T, a time (start of test interval)
o Tf, a time (end of test interval)
o K, the number of packets sent from the source during the test
interval
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o J[n], the number of packets received at a particular Receiver, n,
where 1<=n<=N
o lambda, a rate in reciprocal seconds (for Poisson Streams)
o incT, the nominal duration of interpacket interval, first bit to
first bit (for Periodic Streams)
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)
o TstampSrc, the wire time of the packet as measured at MP(Src) (the
Source Measurement Point)
o TstampRecv, the wire time of the packet as measured at MP(Recv),
assigned to packets that arrive within a "reasonable" time
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
o dT, shorthand notation for a oneway delay singleton value
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.
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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.
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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)
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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 =
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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.
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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
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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
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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.
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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
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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 addresses may corrupt the
results without any possibility to detect the spoofing.
9.2. onetogroup metric
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.
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11. IANA Considerations
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] :
IANA is asked to register the following metrics in the IANAIPPM
METRICSREGISTRYMIB :
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
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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
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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
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:= { 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."
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 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.
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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.
[RFC3357] Koodli, R. and R. Ravikanth, "Oneway Loss Pattern Sample
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@orangeftgroup.com
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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
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