Internet Research Task Force D. Chen
Internet-Draft H. Yang
Intended status: Informational K. Yao
Expires: September 6, 2022 China Mobile
G. Fioccola
Huawei Technologies
March 05, 2022
Network measurement intent - one of IBN use cases
draft-yang-nmrg-network-measurement-intent-04
Abstract
As an important technical means to detect network state, network
measurement has attracted more and more attention in the development
of network. However, the current network measurement technology has
the problem that the measurement method and the measurement purpose
cannot match well. To solve this problem, this memo introduces
network measurement intent, namely the process of realizing user or
network operator to allocate network states as needed. And it can be
as a specified user case of intent based network.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
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Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on September 6, 2022.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Definitions and Acronyms . . . . . . . . . . . . . . . . . . 3
3. Connections to Existing Documents . . . . . . . . . . . . . . 3
4. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 5
5. Concrete Examples . . . . . . . . . . . . . . . . . . . . . . 7
5.1. SLA measurement intent . . . . . . . . . . . . . . . . . 8
5.2. Clustered performance measurement intent . . . . . . . . 10
6. Classification of NMI . . . . . . . . . . . . . . . . . . . . 11
6.1. Static NMI . . . . . . . . . . . . . . . . . . . . . . . 12
6.2. Dynamic NMI . . . . . . . . . . . . . . . . . . . . . . . 12
7. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
8. Security Considerations . . . . . . . . . . . . . . . . . . . 12
9. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
10.1. Normative References . . . . . . . . . . . . . . . . . . 13
10.2. Informative References . . . . . . . . . . . . . . . . . 13
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 13
1. Introduction
With the rapid development of the current network, the scale of the
network is getting larger and larger, while users' requirements for
the network are getting higher and higher. At the same time, network
resources are increasingly restrained. In order to realize the
efficient allocation of network resources, it is necessary to
understand the running state of the network, and network measurement,
as a technical means to detect the network, has been paid of more and
more attention. The continuous development of network measurement
technology has also satisfied the higher and higher precision of
network perception. However, both the traditional network
measurement technology and the network telemetry technology, which
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has emerged with the development of software-defined network in
recent years, need to occupy the network resources when detecting the
network state and feeding back the detection results. Therefore, to
some extent, the choice of network measurement methods, in addition
to different accuracy of measurement results, will also cause
different degrees of burden to the network.
In order to balance the accuracy of network measurement results with
the network load, it is very important to choose the appropriate
network measurement method according to the different requirements of
network measurement. As a result, accurate on-demand network
measurement technology is becoming more and more important. At the
same time, the development of Intent based Network (IBN) enables the
network to be configured according to users' or network
administrators' intent. Therefore, we can combine network
measurement with IBN, that is, the users' or network administrators'
perceived demand for network state is regarded as network measurement
intent.
We want to use the network measurement intent to achieve network
performance acquisition based on user/network administrator intent-
based, verify whether network measurement results meet the
measurement intent, and further improve the accuracy of the
configuration in IBN.
2. Definitions and Acronyms
CLI: Command-line Interface.
IBN: Intent based Network.
Policy: A set of rules that governs the choices in behavior of a
system.
NMI: Network Measurement Intent, refers to based on user/network
operator's demand for network status, and automatically collect
network status information on demand.
SLA: Service Level Agreement.
3. Connections to Existing Documents
As the rise of IBN, different groups have different definitions of
intent. For example, ONF [ONOS] defines intent is represented as a
list of CLI modes that allows users to pass low-level details on the
network; and there are two active RG drafts in the NMRG right now,
Intent-Based Networking - Concepts and Definitions,
[I-D.irtf-nmrg-ibn-concepts-definitions] solves the problem that
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"What is an intent?"
and[I-D.irtf-nmrg-ibn-intent-classification]solves the problem "Given
a specific intent, how to parse/disassemble it from different
angles?".
Naturally, the question that needs to be solved after concept
definition should be "How to realize an specific intent?". The
classification draft can be considered as the first step of
realization of a given intent, however, it is not enough. Some other
issues should be clarified, like"whether the input intent is valid or
not?" , "What would the IBN system do when the result is not
acceptable?", "If the result is not acceptable, does human/operator
interference required?"... We should take a specific IBN use case
for illustration of the realization procedure, so we will take the
network measurement intent as an example.
Referring to the taxonomy of intent proposed
in[I-D.irtf-nmrg-ibn-concepts-definitions], the network measurement
intent can be classified into different subgroups.
Solution: the intent could cover carrier and data center.
Intent user type: customer.
Intent type: customer service intent.
Intent scope: Application, QoS.
Network scope: Radio Access, Transport, Edge, Core.
Abstraction: Non-technical.
Lifecycle Requirements: transient.
In order to combine the NMI with the existing drafts of IBN, in this
document we define the components of the NMI processing process as
follows:
o NMI Recognition and Acquisition
o NMI Translation
o NMI Policy
o NMI Orchestration and pre-Verification
o Data Collection and Analytics
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o NMI Compliance Assessment
4. Overview
As mentioned above, NMI refers to the on-demand measurement of the
network state based on the user/network operators' perceived intent
of the network state. We will present the detailed process of it
within each part and take the measurement of busy network
performances as a simple example.
o NMI Recognition and Acquisition.
* In this function, NMI will be recognized by "ingesting" users'
or network operators' measurement intent. They have the
ability to identify the NMI of a certain network performance
that users want to measure, such as delay, jitter, etc., and at
the same time allow users to express the NMI of network
performance in a variety of interactive ways to ensure the
accuracy of the identification of the NMI. To achieve this
functionality, such an interaction requires the use of the
intent-northbound interface defined in the IBN.
o NMI Translation.
* In this function, NMI needs to be translated into corresponding
measurement policy, which includes but is not limited to
network performance parameters to be measured (such as delay,
jitter, and packet loss), time period to be measured, and
measurement precision. For a simple example, in the
measurement of busy network performances, due to dynamic
changes such as daily network bandwidth occupancy rate, the
period of network busy time is not fixed. As a result, NMI
Policy generated by NMI Translation can determine the threshold
when the network state is busy on the same day based on the
historical data learned by AI.
o NMI Policy
* In this function, NMI policy needs to be translated into
actions and requests taken against the specified network
element. Therefore, NMI policy generated by NMI Translation
must be executable, that is, corresponding underlying network
devices must be able to support policy execution.. If the
generated policy cannot be executed by the underlying device,
the policy needs to be adjusted. And if the measurement
results cannot meet the requirements, the policy also needs to
be adjusted.
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o NMI Orchestration and pre-Verification.
* In this function, according to the previous NMI Translation and
NMI Policy step, NMI Orchestration and pre-Verification
determines the measurement scheme according to the measurement
policy generated by NMI Policy, and pre-verifies whether the
measurement scheme is feasible.
* Take busy time network measurement as an example, except for
choosing of measurement schemes and contents, it also needs to
determine whether the network is busy according to the current
network state. In addition, this function performs automatic
network deployment, such as in CLI mode.
o Data Collection and Analytics.
* In NMI, data collection and analysis should be based on the
selected measurement scheme and the content to be measured that
determined in previous steps, automatically realize the
collection on demand, and generate corresponding data analysis
results.
o NMI Compliance Assessment.
* At the end, this function verifies whether the results meets
the requirement and whether the NMI is satisfied. If either of
the two conditions is not satisfied, the NMI should be modified
and re-enter the NMI Policy.
And he measurement flow diagram is shown as the following figure:
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+ ^
NMI input| |
+---------v-------+ |
| NMI Recognition | |Measurement
| and Acquistion | |Results
+--------+--------+ |Feedback
| |
+--------v--------+ |
| NMI Translation | |
+--------+--------+ |
| +---+----- -----+
+--------v--------+ |NMI Compliance |
| NMI Policy <------+Assessment |
+--------+--------+ +--^------------+
| |
+---------v-----------+ +--+--------------+
| NMI Orchestration | | Data Collection |
| and pre+Verification| | and Analytics |
+---------+-----------+ +--^--------------+
| |
+---v------------------+---+
| Network Infrastructure |
+--------------------------+
5. Concrete Examples
In this section, we will take SLA measurement intent as an example to
illustrate each step of the process.
With the development of measurement technology in recent years,
network measurement can be divided into active measurement, passive
measurement and a combination of active and passive measurement. As
mentioned above, no matter which measurement technology will occupy
network resources. For example, if the transmission frequency of
active measurement message is too fast, it will occupy too much
bandwidth resources and affect the normal operation of actual
business. While if the transmission frequency is too slow, some
instantaneous network anomalies will be missed and the network status
cannot be accurately reflected. Passive measurement requires real-
time collection of actual business data. If the sampling rate is too
high, a large amount of data will be accumulated in a short time.
The analysis system for real-time analysis of these data needs strong
processing capacity; if the sampling rate is too low, some network
anomalies will also be omitted.
How to balance and accurately measure the network state, especially
the abnormal network affecting the service, while occupying as little
network bandwidth as possible, and the processing capacity of the
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data analysis system is not high, this is the function that the NMI
scheme based on IBN should realize.
In this section, we will consider two examples to illustrate each
step of the process.
5.1. SLA measurement intent
Taking network SLA performance index -- time delay measurement as an
example, the simple schematic diagram is as follows, different
thresholds, warning value and alert value should be set for network
delay in advance. When the delay value is below warning, the network
is normal and the business is normal. When the delay is between
warning value and alert value, the network fluctuation is abnormal,
but the business is normal. When the delay exceeds the alert value,
both the network and business are abnormal. For delay in different
thresholds, different measurement strategies should be adopted:
o When the network delay exceeds the alert value, or when the
historical data predict that the delay will exceed the alert
value, passive measurement requires 100% sampling of business
data, and the transmission frequency of active measurement is
modulated to the maximum. At the same time, the log and alarm
data of the whole network equipment are collected to realize the
most fine-grained measurement of the network, locate the root
cause of the problem and repair the network in time.
o When the network delay exceeds warning value but is lower than
alert value, passive measurement samples 60% of business data, and
the transmission message frequency of the active measurement is
adjusted to the median value, and the running state data of some
key devices in the network is collected synchronously.
o When the network delay is less than warning value, passive
measurement data is sampled at 20%, and active measurement message
frequency is adjusted to the lowest, and the network equipment
running state of key nodes can be collected as needed.
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^ms
|
|
| XX
| X X Sampling Rate 100%
| XX X
alert +--------------------------------------------------------+
| X X Sampling Rate 60%
| X XX
| X X XX
| XX X X XXX
| XXX X X X X
| XX X X X X XX
| X XX X X XX XX X XX
warning +-------------------------------------------------------+
| X XX X XX X XX X XX XX
| XX X X X X XX XX X X
| XX X X X X X XX XXX X
| X XX XXX X XX X
| X XX XX X
| X XX Sampling Rate 20%
|
+----------------------------------------------------------->
Based on the above SLA time delay index measurement, different
thresholds adopt different measurement strategies, the concrete steps
of SLA measurement intent are as follows:
o In NMI Recognition and Acquisition, SLA measurement intent is
recognized, and business requirements and performance metrics are
identified by interacting with users. Then the NMI Recognition
and Acquisition module inputs the SLA measurement intent into the
NMI Translation module.
o The NMI Translation module combines the SLA measurement intent
with the measurement policy in NMI Policy, and outputs the
executable measurement policy, such as the message transmission
frequency of active measurement, the sampling rate of passive
measurement, the collection range of equipment running state, etc.
o The NMI Orchestration and pre-Verification module arranges the
measurement policy into the specific configuration and execution
time of each device in the tested network. The NMI Orchestration
and pre-Verification module verifies the implementation of the
policy in the equipment and preanalyzes the measurement results.
o The Data Collection and Analysis module will collect the
measurement data according to the requirements of the previous
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step, make a simple analysis of the collected data, and then send
the collected measurement data to the NMI Compliance Assessment
module. After that, it feedback the measurement results to the
user to complete the closed loop of the measurement task.
o According to the change of delay data in the measured data, the
NMI Compliance Assessment module notifies the NMI Orchestration
and pre-Verification module to modify the execution time of the
policy in time, and at the same time updates the measured results
to the delay history database to improve the accuracy of delay
prediction. The NMI Compliance Assessment module evaluates
whether the actual measurement results are in line with the user's
intent. If they are, the results will be fed back. If they are
not, the NMI Policy module will be informed to adjust the policy,
and then the measurement will be restarted.
5.2. Clustered performance measurement intent
The desired approach is to accurately measure the network state,
especially when there are some issues affecting the service, but at
the same time, reduce the resources to be employed to achieve the
desired accuracy.
In this regard, the Clustered Alternate-Marking framework [RFC8889]
adds flexibility to Performance Management (PM), because it can
reduce the order of magnitude of the packet counters. This allows
the NMI Orchestration and pre-Verification module to supervise,
control, and manage PM in large networks.
RFC 8889 [RFC8889] introduces the concept of cluster partition of a
network. The monitoring network can be considered as a whole or
split into clusters that are the smallest subnetworks (group-to-group
segments), maintaining the packet loss property for each subnetwork.
The clusters can be combined in new connected subnetworks at
different levels, forming new clusters, depending on the level of
detail to achieve.
The clustered performance measurement intent represents the spatial
accuracy, that is the size of the subnetworks to consider for the
monitoring. It is possible to start without examining in depth and,
in case of necessity, the "network zooming" approach can be used.
This approach called "network zooming" and can be performed in two
different ways:
1. change the traffic filter and select more detailed flows;
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2. activate new measurement points by defining more specified
clusters.
The network-zooming approach implies that some filters, rules or flow
identifiers are changed. But these changes must be done in a way
that do not affect the performance. Therefore there could be a
transient time to wait once the new network configuration takes
effect. Anyway, if the performance issue is relevant, it is likely
to last for a time much longer than the transient time.
The concrete steps of the clustered performance measurement intent
are as follows:
o In NMI Recognition and Acquisition, the clustered performance
measurement intent is recognized. Then the NMI Recognition and
Acquisition module inputs the clustered performance measurement
intent into the NMI Translation module.
o The NMI Translation module analyzes the clustered performance
measurement intent and outputs the executable measurement policy,
such as network partition and the spatial accuracy for the
monitoring.
o The NMI Orchestration and pre-Verification module arranges and
calibrates the measurement with the specific configuration to
split the whole network into clusters at different levels.
o The Data Collection and Analysis module collects the measurement
data from the different clusters, and then send these data to the
NMI Compliance Assessment module. It verifies the performance for
each cluster and send the measurement results to the user.
o The NMI Compliance Assessment module, in case a cluster is
experiencing a packet loss or the delay is high, notifies the NMI
Orchestration and pre-Verification module to modify the cluster
partition of the network for further investigation. The network
configuration can be immediately modified in order to perform a
new partition of the network but only for the cluster with bad
performance. In this way, the problem can be localized with
successive approximation up to a flow detailed analysis. This is
the so-called "closed loop" performance management.
6. Classification of NMI
In this section, we divide the network measurement intent into static
NMI and dynamic NMI according to different requirement
characteristics.
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6.1. Static NMI
Static NMI refers to the measurement purposes remain unchanged and is
independent of the network state/external environment. Static NMI
can be translated into determined network performance indicator
values, such as concrete delay values, network bandwidth occupancy,
throughput and so on.
Because the static NMI can be translated into the measurement of the
determined network performance parameters, the whole process is
relatively simple and error-prone, and only needs to verify whether
the measurement results meet the requirements.
6.2. Dynamic NMI
Dynamic NMI refers to the measurement purpose remains unchanged but
the measurement process changes dynamically according to the network
state/external environment. Dynamic NMI can also be translated into
the measurement of determined network performance parameters,
however, the values of network performance parameters will change
with the changes of network states and external environment.
For example, the measurement of busy network performances mentioned
in the previous. Although the corresponding network parameters for
judging whether the network is busy are determined, the corresponding
network parameters have different values according to different
network states and external environments.
Due to the dynamic nature of dynamic NMI, its processing process is
more complex than static NMI. It is not only necessary to verify the
accuracy of demand analysis, but also to verify whether the final
measurement results meet the requirements.
7. Summary
This memo introduces the network measurement intent, and give two
concrete examples to illustrate the process of network measurement
intent. On the basis of existing intent drafts, this memo can be
used as a use case for IBN. NMI is a big and typical use case of
IBN, and the classification of different examples of NMI may vary.
8. Security Considerations
TBD.
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9. IANA Considerations
This document has no requests to IANA.
10. References
10.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC8889] Fioccola, G., Ed., Cociglio, M., Sapio, A., and R. Sisto,
"Multipoint Alternate-Marking Method for Passive and
Hybrid Performance Monitoring", RFC 8889,
DOI 10.17487/RFC8889, August 2020,
<https://www.rfc-editor.org/info/rfc8889>.
10.2. Informative References
[I-D.irtf-nmrg-ibn-concepts-definitions]
Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
Tantsura, "Intent-Based Networking - Concepts and
Definitions", draft-irtf-nmrg-ibn-concepts-definitions-06
(work in progress), December 2021.
[I-D.irtf-nmrg-ibn-intent-classification]
Li, C., Havel, O., Olariu, A., Martinez-Julia, P., Nobre,
J. C., and D. R. Lopez, "Intent Classification", draft-
irtf-nmrg-ibn-intent-classification-06 (work in progress),
February 2022.
Authors' Addresses
Danyang Chen
China Mobile
Beijing 100053
China
Email: chendanyang@chinamobile.com
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Hongwei Yang
China Mobile
Beijing 100053
China
Email: yanghongwei@chinamobile.com
Kehan Yao
China Mobile
Beijing 100053
China
Email: yaokehan@chinamobile.com
Giuseppe Fioccola
Huawei Technologies
Riesstrasse, 25
Munich 80992
Germany
Email: giuseppe.fioccola@huawei.com
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