Internet DRAFT - draft-yang-nmrg-network-measurement-intent
draft-yang-nmrg-network-measurement-intent
Internet Research Task Force D. Chen
Internet-Draft H. Yang
Intended status: Informational K. Yao
Expires: 27 April 2023 China Mobile
G. Fioccola
Q. Wu
Huawei
LM. Contreras
Telefonica
24 October 2022
Network measurement intent - one of IBN use cases
draft-yang-nmrg-network-measurement-intent-06
Abstract
As an important technical mean to detect network state, network
measurement has attracted more and more attention in the development
of networks. 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, presents a process of scheduling the
network resource and measurement task to meet the user or network
operator's needs. And it can be seen as a specific use 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
working documents as Internet-Drafts. The list of current Internet-
Drafts is at https://datatracker.ietf.org/drafts/current/.
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."
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This Internet-Draft will expire on 27 April 2023.
Copyright Notice
Copyright (c) 2022 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
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Please review these documents carefully, as they describe your rights
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Definitions and Acronyms . . . . . . . . . . . . . . . . . . 3
3. Relationship to Existing Documents . . . . . . . . . . . . . 4
4. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 5
5. Concrete Examples . . . . . . . . . . . . . . . . . . . . . . 7
5.1. Time Accuracy Measurement . . . . . . . . . . . . . . . . 7
5.2. Spatial Accuracy Measurement . . . . . . . . . . . . . . 10
6. Classification of NMI . . . . . . . . . . . . . . . . . . . . 12
6.1. Static NMI . . . . . . . . . . . . . . . . . . . . . . . 12
6.2. Dynamic NMI . . . . . . . . . . . . . . . . . . . . . . . 12
7. Security Considerations . . . . . . . . . . . . . . . . . . . 13
8. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 13
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 13
9.1. Normative References . . . . . . . . . . . . . . . . . . 13
9.2. Informative References . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
1. Introduction
With the rapid growth of the present network, the scale of the
network increases, while users' service requirements for the network
are getting stricter and more diversified, e.g., being both loss
requirements and throughput needs to be met simultaneously. At the
same time, the growth of network resources is hard to meet the
service requirements of users. In order to meet the needs of network
development, many new network technologies have emerged. The rise
and development of intention network is one of it, which brings many
advantages to the development of network. In this memo, we presented
two use cases for intent based network: network measurement intent
and interconnection intent. In order to make good usage of network
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resources and improve utilization of the bandwidth, it becomes
necessary to understand the current running state of the network, and
collect network measurements, as technical means to detect the
network resource changes. As an important technical mean to detect
network state, network measurement has attracted more and more
attention in the development of networks. The continuous development
of network measurement technology has also increased higher precision
of network awareness. However, both the traditional network
measurement technology (e.g., loss measurement and delay measurement
defined inRFC 2679 [RFC2679]RFC 2680 [RFC2680]) and the network
telemetry technology RFC 8639 [RFC8639]RFC 8641
[RFC8641][I-D.ietf-netconf-adaptive-subscription], which has emerged
with the development of software-defined network in recent years,
need to consume more network resources when detecting the network
state changes 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 level of network load 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. Besides,
the current network measurement technology has the problem that the
measurement method and the measurement purpose cannot match well.
Our proposed approach is to use the network measurement intent to
achieve network performance acquisition based on user/network
administrator intent- , 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.
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3. Relationship to Existing Documents
As the rise of IBN, different groups have different definitions of
The 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
"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?".[I-D.irtf-nmrg-ibn-intent-classification]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-intent-classification], the network measurement
intent can be classified into different categories.
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 integrate the NMI with the IBN, in this document we
define the components of the NMI interactive process as follows:
* NMI Recognition and Acquisition
* NMI Translation
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* NMI Policy
* NMI Orchestration and pre-Verification
* Data Collection and Analytics
* 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.The user/network operators' perceived intent is
usually in the form of service level objective or service level
expectation. We will take the measurement of the performance of the
network overwhelming with the network traffic as a simple example and
present the detailed interactive process for those components defined
in section 3.
* 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,e.g., service
interface model in [RFC8299][RFC8466] or intent interface
defined in [TMF1253A].
* 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 unit. For a simple example, in the measurement of
busy network performances, due to dynamic changes of network
characteristics, such as daily network bandwidth utilization
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 or the network is
congested on the same day based on the historical data learned
by AI.
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* NMI Policy
- In this function, NMI policy needs to be translated into
actions and instructioninvoked 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 service requirements set by the users
and network operators, the policy also needs to be adjusted.
* 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, besides
choosing of measurement schemes and assigning measurement tasks
[RFC8639][RFC8641][I-D.ietf-netconf-adaptive-subscription][RFC8
194][I-D.ietf-netmod-eca-policy], it also needs to determine
whether the network is busy according to the current network
state. In addition, this function performs automatic network
deployment,e.g.,using model driven network management approach
defined in [RFC8969].
* Data Collection and Analytics.
- In NMI, data collection and analysis should be based on the
selected measurement scheme and parameters set to be measured
that determined in previous steps, automatically realize the
collection on demand, and generate corresponding data analysis
results.
* NMI Compliance Assessment.
- At the end, this function verifies whether the results meets
the service 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 Acquisition | |Results
+--------+--------+ |Feedback
| |
+--------v--------+ |
| NMI Translation | |
+--------+--------+ |
| +---+----- -----+
+--------v--------+ |NMI Compliance |
| NMI Policy <------+Assessment |
+--------+--------+ +--^------------+
| |
+---------v-----------+ +--+--------------+
| NMI Orchestration | | Data Collection |
| and pre-Verification| | and Analytics |
+---------+-----------+ +--^--------------+
| |
+---v------------------+---+
| Network Infrastructure |
+--------------------------+
Figure 1: Full Lifecycle of NMI
5. Concrete Examples
In this section, we will take time accuracy measurement intent and
spatial accuracy measurement as examples to illustrate each step of
the process.
5.1. Time Accuracy Measurement
With the development of measurement technology in recent years,
network measurement methods can be divided into active measurement,
passive measurement and a hybrid measurement [RFC7799]. No matter
which measurement technology is used, the network resource
consumption will be influenced by the network condition and change
over the time.e.g.,, 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
[I-D.ietf-netconf-adaptive-subscription].The analysis system for
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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
data analysis system is not high, this is the function that the NMI
scheme based on IBN should realize.
Taking network SLA performance metric -- 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:
* 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.
* 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.
* 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%
|
+----------------------------------------------------------->
Figure 2: Network SLA Performance Metric
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:
* 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.
* The NMI Translation module consolidates 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.
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* The NMI Orchestration and pre-Verification module uses the
measurement policy as input and for orchestration layer which is
responsible for translating it 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 pre-analyzes the
measurement results.
* The Data Collection and Analysis module will collect the
measurement data according to the configuration and execution time
requirements of the previous step, make a simple analysis of the
collected data (e.g.,verify the correctness of the measurement
data), and then send the collected measurement data to the NMI
Compliance Assessment module. After that, the NMI Compliance
Assessment module feedbacks the measurement results (e.g., the
measurement results match user intent) to the user to complete the
closed loop of the measurement task.
* 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. According to the measurement
results, 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.
5.2. Spatial Accuracy Measurement
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 Measurement (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.
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[RFC8889] introduces the concept of cluster partition of a network.
The monitored 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;
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:
* 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.
* 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.
* 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.
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* 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.
* 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.
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 utilization,
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-free, 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 section. 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.
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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. Security Considerations
This document introduces the network measurement intent, and uses two
concrete examples to illustrate the process of network measurement
intent. On the basis of existing intent work, this document can be
used as a use case for IBN.
[I-D.irtf-nmrg-ibn-concepts-definitions]provides a comprehensive
discussion of security considerations in the context of IBN, which
are generally applicable also to the network measurement intent
discussed in this document.
8. IANA Considerations
This document has no requests to IANA.
9. References
9.1. 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>.
[RFC2679] Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way
Delay Metric for IPPM", RFC 2679, DOI 10.17487/RFC2679,
September 1999, <https://www.rfc-editor.org/info/rfc2679>.
[RFC2680] Almes, G., Kalidindi, S., and M. Zekauskas, "A One-way
Packet Loss Metric for IPPM", RFC 2680,
DOI 10.17487/RFC2680, September 1999,
<https://www.rfc-editor.org/info/rfc2680>.
[RFC7799] Morton, A., "Active and Passive Metrics and Methods (with
Hybrid Types In-Between)", RFC 7799, DOI 10.17487/RFC7799,
May 2016, <https://www.rfc-editor.org/info/rfc7799>.
[RFC8194] Schoenwaelder, J. and V. Bajpai, "A YANG Data Model for
LMAP Measurement Agents", RFC 8194, DOI 10.17487/RFC8194,
August 2017, <https://www.rfc-editor.org/info/rfc8194>.
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[RFC8299] Wu, Q., Ed., Litkowski, S., Tomotaki, L., and K. Ogaki,
"YANG Data Model for L3VPN Service Delivery", RFC 8299,
DOI 10.17487/RFC8299, January 2018,
<https://www.rfc-editor.org/info/rfc8299>.
[RFC8466] Wen, B., Fioccola, G., Ed., Xie, C., and L. Jalil, "A YANG
Data Model for Layer 2 Virtual Private Network (L2VPN)
Service Delivery", RFC 8466, DOI 10.17487/RFC8466, October
2018, <https://www.rfc-editor.org/info/rfc8466>.
[RFC8639] Voit, E., Clemm, A., Gonzalez Prieto, A., Nilsen-Nygaard,
E., and A. Tripathy, "Subscription to YANG Notifications",
RFC 8639, DOI 10.17487/RFC8639, September 2019,
<https://www.rfc-editor.org/info/rfc8639>.
[RFC8641] Clemm, A. and E. Voit, "Subscription to YANG Notifications
for Datastore Updates", RFC 8641, DOI 10.17487/RFC8641,
September 2019, <https://www.rfc-editor.org/info/rfc8641>.
[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>.
[RFC8969] Wu, Q., Ed., Boucadair, M., Ed., Lopez, D., Xie, C., and
L. Geng, "A Framework for Automating Service and Network
Management with YANG", RFC 8969, DOI 10.17487/RFC8969,
January 2021, <https://www.rfc-editor.org/info/rfc8969>.
9.2. Informative References
[I-D.ietf-netconf-adaptive-subscription]
Wu, Q., Song, W., Liu, P., Ma, Q., Wang, W., and Z. Niu,
"Adaptive Subscription to YANG Notification", Work in
Progress, Internet-Draft, draft-ietf-netconf-adaptive-
subscription-00, 23 June 2022,
<https://www.ietf.org/archive/id/draft-ietf-netconf-
adaptive-subscription-00.txt>.
[I-D.ietf-netmod-eca-policy]
Wu, Q., Bryskin, I., Birkholz, H., Liu, X., and B. Claise,
"A YANG Data model for ECA Policy Management", Work in
Progress, Internet-Draft, draft-ietf-netmod-eca-policy-01,
19 February 2021, <https://www.ietf.org/archive/id/draft-
ietf-netmod-eca-policy-01.txt>.
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[I-D.irtf-nmrg-ibn-concepts-definitions]
Clemm, A., Ciavaglia, L., Granville, L. Z., and J.
Tantsura, "Intent-Based Networking - Concepts and
Definitions", Work in Progress, Internet-Draft, draft-
irtf-nmrg-ibn-concepts-definitions-09, 24 March 2022,
<https://www.ietf.org/archive/id/draft-irtf-nmrg-ibn-
concepts-definitions-09.txt>.
[I-D.irtf-nmrg-ibn-intent-classification]
Li, C., Havel, O., Olariu, A., Martinez-Julia, P., Nobre,
J. C., and R. Diego Lopez, "Intent Classification", Work
in Progress, Internet-Draft, draft-irtf-nmrg-ibn-intent-
classification-08, 18 May 2022,
<https://www.ietf.org/archive/id/draft-irtf-nmrg-ibn-
intent-classification-08.txt>.
Authors' Addresses
Danyang Chen
China Mobile
Beijing
100053
China
Email: chendanyang@chinamobile.com
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
Riesstrasse, 25
80992 Munich
Germany
Email: giuseppe.fioccola@huawei.com
Chen, et al. Expires 27 April 2023 [Page 15]
Internet-Draft Network Working Group October 2022
Qin Wu
Huawei
101 Software Avenue, Yuhua District
Nanjing
210012
China
Email: bill.wu@huawei.com
Luis M. Contreras
Telefonica
28050 Madrid
Spain
Email: luismiguel.contrerasmurillo@telefonica.com
Chen, et al. Expires 27 April 2023 [Page 16]
