Enhanced Use Cases for Scaling Deterministic Networks
draft-zhao-detnet-enhanced-use-cases-01
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| Document | Type | Active Internet-Draft (individual) | |
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| Authors | Junfeng Zhao , Quan Xiong , Zongpeng Du | ||
| Last updated | 2024-10-18 | ||
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draft-zhao-detnet-enhanced-use-cases-01
DETNET J. Zhao
Internet-Draft CAICT
Intended status: Standards Track Q. Xiong
Expires: 21 April 2025 ZTE Corporation
Z. Du
China Mobile
18 October 2024
Enhanced Use Cases for Scaling Deterministic Networks
draft-zhao-detnet-enhanced-use-cases-01
Abstract
This document describes use cases and network requirements for
scaling deterministic networks which is not covered in RFC8578, such
as industrial internet, high experience video and intelligent
computing, and outlines the common properties implied by these use
cases.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on 21 April 2025.
Copyright Notice
Copyright (c) 2024 IETF Trust and the persons identified as the
document authors. All rights reserved.
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This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents (https://trustee.ietf.org/
license-info) in effect on the date of publication of this document.
Please review these documents carefully, as they describe your rights
and restrictions with respect to this document. Code Components
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Requirements Language . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Enhanced Use Cases and Network Requirements . . . . . . . . . 4
3.1. Industrial Internet . . . . . . . . . . . . . . . . . . . 4
3.1.1. Use Case Description . . . . . . . . . . . . . . . . 4
3.1.1.1. Machine Vision . . . . . . . . . . . . . . . . . 4
3.1.1.2. Remote Control . . . . . . . . . . . . . . . . . 5
3.1.1.3. AGV Intelligent Control . . . . . . . . . . . . . 6
3.1.1.4. AR Assistance . . . . . . . . . . . . . . . . . . 6
3.1.2. Requests to the IETF . . . . . . . . . . . . . . . . 7
3.2. High Experience Video . . . . . . . . . . . . . . . . . . 8
3.2.1. Use Case Description . . . . . . . . . . . . . . . . 8
3.2.1.1. Cloud VR and AR . . . . . . . . . . . . . . . . . 8
3.2.1.2. Cloud Games . . . . . . . . . . . . . . . . . . . 9
3.2.1.3. Cloud Live Streaming . . . . . . . . . . . . . . 10
3.2.2. Requests to the IETF . . . . . . . . . . . . . . . . 10
3.3. Intelligent Computing . . . . . . . . . . . . . . . . . . 10
3.3.1. Use Case Description . . . . . . . . . . . . . . . . 11
3.3.1.1. Scientific Research . . . . . . . . . . . . . . . 11
3.3.1.2. Autonomous Vehicles . . . . . . . . . . . . . . . 11
3.3.2. Requests to the IETF . . . . . . . . . . . . . . . . 12
4. Use Case Common Themes . . . . . . . . . . . . . . . . . . . 12
4.1. Differentiated Deterministic Requirements . . . . . . . . 13
5. Security Considerations . . . . . . . . . . . . . . . . . . . 14
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 14
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 14
8.1. Normative References . . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
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1. Introduction
According to [RFC8655], Deterministic Networking (DetNet) operates at
the IP layer and delivers service which provides extremely low data
loss rates and bounded latency within a network domain. The bounded
latency indicates the minimum and maximum end-to-end latency from
source to destination and bounded jitter (packet delay variation).
[RFC8578] has presented use cases for diverse industries and these
use cases differ in their network topologies and requirements. It
should provide specific desired behaviors in DetNet.
[I-D.ietf-detnet-scaling-requirements] focus on the scaling
deterministic networks and describes the enhanced requirements for
DetNet enhanced data plane including the deterministic latency
guarantees and it also mentioned the enhanced DetNet should support
different levels of application requirements which is important for
the DetNet deployment. There are a variety of use cases in scaling
deterministic networks which is not covered in [RFC8578]. It is
required to provide the typical use cases for scaling deterministic
networks and analyze the SLAs requirements and desired behaviors in
enhanced DetNet.
The industries covered by the use cases in this document are:
* Industrial Internet (section 3.1)
* High Experience Video (section 3.2)
* Intelligent Computing (section 3.3)
This document describes use cases and network requirements for
scaling deterministic networks including industrial internet, high
experience video and intelligent computing and outlines the common
properties implied by these use cases.
1.1. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
2. Terminology
The terminology is defined as [RFC8655] and [RFC8578].
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3. Enhanced Use Cases and Network Requirements
3.1. Industrial Internet
3.1.1. Use Case Description
In the industrial internet, the entire industrial process can be
roughly divided into research and development design, production
manufacturing, operation and maintenance services. The typical
application prospects of deterministic networks mainly include ultra-
high definition video, cloud-based robots, remote control, machine
vision, and cloud-based AGV. The scenarios such as machine vision,
AGV intelligent control, remote control, and AR assisted robotic arm
control demand deterministic requirements.
3.1.1.1. Machine Vision
The machine vision system needs to achieve real-time remote
monitoring function, which requires high-speed and large connectivity
characteristics. It can monitor the production process execution
management system (MES) of manufacturing enterprises through mobile
and portable terminals without entering the workshop, and obtain the
operating status of the visual inspection system, such as normal
operating time, effective operating time, fault cause etc. It is
bandwidth sensitive and demand cloud-based deployment and wide area
networks requirements.
The following table shows the main network requirements of machine
vision.(These metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP
TR 22.261, and 3GPP TR 22.829.)
+---------------------------------+---------------------------------+
| Machine Vision Requirement | Attribute |
+---------------------------------+---------------------------------+
| Bandwidth | Real time upload of image |
| | information:>50M |
| | |
| One-way maximum delay | 10 ms |
| | |
| Availability | 99.99% |
+---------------------------------+---------------------------------+
Figure 1: Requirements of Machine Vision
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3.1.1.2. Remote Control
Remote control can ensure personnel safety, improve production
efficiency, and achieve assistance from multiple production units.
In order to achieve the effect of remote control, the controller
needs to send status information to the controller through a
communication network based on remote perception. The controller
analyzes and makes decisions based on the received status
information, and then sends corresponding action instructions to the
controller through the communication network. The controller
executes the corresponding actions based on the received action
instructions, completing the remote control process. In order to
guarantee control effectiveness, communication network latency,
jitter, and reliability are even more important. The typical
application is cloud-based PLC (Programmable Logic Controller). It
is jitter sensitive and cloud-based PLC demand wide area networks
requirements.
The following table describes requirements of Cloud-based PLC.
(These metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP TR
22.261, and 3GPP TR 22.829.)
+-------------------------------+-----------------------------------+
| Cloud-based PLC Requirement | Attribute |
+-------------------------------+-----------------------------------+
| Bandwidth | Image/video stream upload, |
| | upstream>50Mbps; |
| | PLC control command issued, |
| | downstream>50kbps; |
| | |
| One-way maximum delay |Within workshop level equipment:1ms|
| |Workshop level equipment room:10ms |
| |Remote operation in the park/city/ |
| |wide area: image upstream:20ms; |
| |Command issuance:10ms; |
| | |
| Maximum jitter | Less than 100 us |
| | |
| Availability | 99.999% |
+-------------------------------+-----------------------------------+
Figure 2: Requirements of Cloud-based PLC
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3.1.1.3. AGV Intelligent Control
Automated Guided Vehicle (AGV) is an intelligent device widely used
in highly automated places such as factory workshops, airports,
ports, freight warehouses, etc. It generally consists of three
parts: walking, navigation, and control systems. The automated AGV
is equipped with a camera to capture the scene in front of the
vehicle and upload it to the MEC and navigation system in real-time
through a 5G module for image analysis and route planning, achieving
fully automated logistics transportation. AGV has a certain driving
speed and is often used in cluster operation scenarios. Therefore, a
network connection with high deterministic delay and jitter is
required to transmit control signals.
The following table describes requirements of AGV intelligent
control.(These metrics are based on 3GPP Standard 3GPP TS 22.104,
3GPP TR 22.261, and 3GPP TR 22.829.)
+-----------------------------+--------------------------------------+
| AGV Intelligent Control | |
| Requirement | Attribute |
+-----------------------------+--------------------------------------+
| Bandwidth |Schedule communication:>1Mbps, |
| |Real time communication:1Mbps~200Mbps |
| |Visual: 10Mbps~1Gbps |
| | |
| One-way maximum delay |Schedule communication:100ms |
| |Dispatching communication:100ms |
| |Real time communication:20ms~40ms |
| |Visual: 10ms~100ms |
| Availability | 99.9999% |
+-----------------------------+--------------------------------------+
Figure 3: Requirements of AGV Intelligent Control
3.1.1.4. AR Assistance
With the intelligent and networked transformation and upgrading of
industrial manufacturing equipment, more and more AR assisted
intelligent robots will be used in advanced manufacturing. At the
same time, there are scenarios where multiple robot systems work
together, such as welding, stamping, etc. The robotic arm is the
most widely used automated mechanical device in the field of robotics
technology, in areas such as industrial manufacturing, medical
treatment, entertainment services, military, semiconductor
manufacturing, and space exploration. The more axis joints of the AR
assisted robotic arm, the higher the degree of freedom, and the
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larger the angle of the operating range.
The following table describes requirements of AR Assistance. (These
metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP TR 22.261,
and 3GPP TR 22.829.)
+---------------------------+----------------------------+
| AR Assistance Requirement| Attribute |
+---------------------------+----------------------------+
| Bandwidth | Maintenance guidance: |
| | downstream>50Mbps |
| | upstream > 20Mbps |
| | downstream>50kbps |
| | Auxiliary assembly: >50Mbps|
| | downstream: 1Mbps~30Mbps |
| | |
| One-way maximum delay |Maintenance guidance:20ms |
| |Auxiliary assembly:10ms |
| | |
| Maximum jitter | Less than 500 us |
| | |
| Availability | 99.999% |
+---------------------------+----------------------------+
Figure 4: Requirements of AR Assistance
3.1.2. Requests to the IETF
* Real-time remote monitoring, which requires high-speed
connectivity
* Cloud-based deployment, which requires transmission through
heterogeneous networks
* Cloud-based centralized management
* Remote control is jitter sensitive, e.g. less than 100us
* Industrial camera images with high definition, with little or no
compression, which requires high bandwidth
* Low end-to-end delay requirements differ from applications and
services, such as 10ms and 20ms
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3.2. High Experience Video
3.2.1. Use Case Description
High Experience Video refers to video content that delivers an
exceptional viewing experience through advanced technologies and
production techniques. It demands high-quality transmission to
ensure that the content is delivered without compromising its
integrity and impact. High Experience Video relies on deterministic
networks to deliver the best possible viewing experience, which
requires a combination of low latency, low jitter, high bandwidth,
and high reliability. The typical scenarios of High Experience Video
involve applications that have high requirements for video quality,
transmission speed, and user experience such as cloud VR and AR,
cloud games and cloud live streaming.
3.2.1.1. Cloud VR and AR
The key feature of Cloud Virtual Reality/Augmented Reality (Cloud VR/
AR) is that content is on the cloud and rendering is on the cloud.
By utilizing powerful cloud capabilities, VR/AR user experience is
improved and terminal costs are reduced. VR/AR will quickly enter
Cloud VR/AR to promote the rapid popularization of VR/AR services.
Cloud AR/VR services exhibit strong latency sensitivity, and
different levels of experience require differentiated certainty.
Cloud VR/AR rendering and streaming latency are divided into three
parts: cloud processing, network transmission, and terminal
processing. Cloud VR/AR operation latency is divided into cloud
rendering latency and terminal secondary rendering and refresh
rendering processes.
The following table describes requirements of Cloud VR/AR. (These
metrics are based on 3GPP TR 22.261).
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+----------------------+-----------+---------------------+----------------+
| Requirement | Bandwidth |One-way maximum delay|Packet loss rate|
+----------------------+-----------+---------------------+----------------+
| Cloud VR/AR Video |downstream | 50ms |no more than |
| comfortable | >75Mbps | |0.001% |
| experience | | | |
+----------------------+-----------+---------------------+----------------+
| Cloud VR/AR Video |downstream | 50ms |no more than |
|comfortable experience|>140Mbps | |0.001% |
|full perspective | | | |
+----------------------+-----------+---------------------+----------------+
| Cloud VR/AR strong |downstream | 15ms |no more than |
|interaction |>260Mbps | |0.001% |
|comfortable experience| | | |
|I frame and P frame | | | |
+----------------------+-----------+---------------------+----------------+
| Cloud VR/AR strong |downstream | 8ms |no more than |
|interaction |1Gbps | |0.0001% |
|8K ideal experience | | | |
|I frame and P frame | | | |
+----------------------+-----------+---------------------+----------------+
Figure 5: The Requirements of Cloud VR/AR
3.2.1.2. Cloud Games
Cloud Game is an online gaming technology based on cloud computing
technology. Cloud gaming technology enables lightweight devices with
relatively limited graphics processing and data computing
capabilities to run high-quality games. In cloud game scenarios,
game related computing is not run on the user terminal, but on a
cloud server, which renders the game scene as a video and audio
stream and transmits it to the user terminal through the network.
The user's cloud gaming experience relies on a high-quality, low
latency network environment.
The following table describes requirements of Cloud Games:
+----------------------+-----------+---------------------+----------------+
| Requirement | Bandwidth |One-way maximum delay|Video resolution|
+----------------------+-----------+---------------------+----------------+
| Junior level | >8Mbps | 150ms |720P |
+----------------------+-----------+---------------------+----------------+
| 3A professional level| >12Mbps | 60ms |1080P |
+----------------------+-----------+---------------------+----------------+
| Level of esports | >40Mbps | 60ms |4K |
+----------------------+-----------+---------------------+----------------+
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Figure 6: Requirements of Cloud Games
3.2.1.3. Cloud Live Streaming
For scenarios such as concerts, press conferences, sports events, and
live events, cloud live streaming uses 5G uplink high bandwidth to
transmit 8K/VR videos. Combined with various applications such as
video analysis based on live streaming services, character and scene
recognition, real-time presentation of athlete and event data, and VR
live streaming interaction, it provides a brand new and rich event
viewing experience.
The following table describes requirements of Cloud live streaming:
+------------------------+---------------------+
| 8K live streaming | Attribute |
| 8K video feedback | |
+------------------------+---------------------+
| Bandwidth | upstream>100Mbps |
| | |
| One-way maximum delay | 200ms |
| | |
| Availability | 99.9% |
| | |
| Frame rate | 60 |
+------------------------+---------------------+
Figure 7: Requirements of Cloud Live Streaming
3.2.2. Requests to the IETF
* High requirements for video quality and transmission speed
* Cloud processing with real-time interaction
* Cloud-based deployment, which requires transmission through
heterogeneous networks
* No jitter requirements
* Packet loss requirement is less than 0.001%
* End-to-end delay requirements differ from applications and
services, such as 8ms, 15ms, 50ms, 150ms, 200ms and so on
3.3. Intelligent Computing
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3.3.1. Use Case Description
Intelligent computing refers to the integration of artificial
intelligence (AI) techniques with computational methods to enhance
the performance, efficiency, and capabilities of computing systems.
It involves the use of algorithms, machine learning models, and other
AI approaches to solve complex problems, analyze large datasets, and
improve decision-making processes. Intelligent Computing has
specific requirements for deterministic networks to ensure reliable
and predictable performance such as predictable latency, low packet
loss rate, high throughput and reliability. The typical scenarios
involve applications such as AI-based scientific research and
autonomous vehicles and so on.
3.3.1.1. Scientific Research
Intelligent computing is used to provide computing and data analysis
capabilities, which are crucial for handling large-scale scientific
simulations and datasets such as astronomy, climate science, and
bioinformatics. In scientific research, a large amount of computing
power resources such as CPU, GPU, memory, and other P-level or higher
are usually required. The network needs to provide services for data
volume of 10G to 100G or above, which requires high bandwidth, high
reliability and high throughput with ultra-low packet loss.
Many applications in scientific research, such as remote
observations, real-time data analysis, and distributed computing,
require networks to provide stable low latency and high reliability.
It must provide millisecond or even microsecond level latency and
jitter guarantees. For example, in nuclear fusion experiments, the
carrier network is required to have 99.999% availability.
3.3.1.2. Autonomous Vehicles
Intelligent computing is used in the development of self-driving
cars, which rely on AI algorithms for perception, decision-making,
and control. Autonomous vehicles refers to the technology of
vehicles that are capable of navigating without the need for human
input such as identifying other vehicles, pedestrians, and traffic
signals. It relies heavily on deterministic forwarding to ensure
safe, efficient, and reliable operation. It is also challenging for
big data management of autonomous driving. Vehicles record data from
4K HD cameras, laser scanners, and radars on the road. Each vehicle
can generate 80TB of data per day, which requires data-intensive
transmission.
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V2X (Vehicle-to-Everything) is a fundamental component of the
autonomous driving ecosystem, providing the necessary communication
backbone that enables vehicles to interact with their environment in
a safe and efficient manner. V2X provides the communication
infrastructure that enables vehicles to exchange information with
each other (V2V), with roadside infrastructure (V2I), with
pedestrians (V2P), and with the network (V2N). This exchange of
information is crucial for autonomous vehicles to make informed
decisions, improve navigation accuracy, and enhance overall road
safety. The following table describes requirements of 5G V2X which
is divided into four scenarios. (These metrics are based on 3GPP TR
22.886)
+----------------------+---------------------+--------------+
| Requirement | Communication Delay | Availability |
+----------------------+---------------------+--------------+
| Vehicles Platooning | 10~25ms | 99%~99.99% |
+----------------------+---------------------+--------------+
| Extended Sensors | 3~100ms | 99%~99.999% |
+----------------------+---------------------+--------------+
| Advanced Driving | 3~100ms | 99%~99.999% |
+----------------------+---------------------+--------------+
| Remote Driving | 5ms | 99.999% |
+----------------------+---------------------+--------------+
Figure 8: The Requirements of Autonomous Vehicles
3.3.2. Requests to the IETF
* Real-time communication
* Data-intensive transmission with high throughput and ultra-low
packet loss
* Low bounded latency, such as us~ms
* High availability, such as 99.999%
4. Use Case Common Themes
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4.1. Differentiated Deterministic Requirements
Classification and characteristics has been summarized from the
requirements of use cases as described in [RFC8578] and this
documents. Seven levels of typical applications have been defined
including on-site production control, remote control, production
monitoring, production collection, video AI, AR/VR high experience
video and intelligent computing. Different levels of applications
differ in the network ranges and SLAs requirements such as bounded
latency, jitter, bandwidth, availability and isolation.
The following table summarizes deterministic requirements of
industrial internet, cloud video and intelligent computing
applications, etc.
+---+------------+--------------------+---------------------------------------------------------+
| | Use Case | Typical | Differentiated Deterministic Requirements |
| | | Applications +----------+----------+---------+-------------------------+
| | | |Bandwidth | Delay | Jitter |Packet Loss| Availability|
+---+------------+--------------------+----------+----------+---------+-----------+-------------+
| 1 |Industrial |Machine Vision | Low | Low | N/A | N/A | Medium |
| |Internet | | | | | | |
| | +--------------------+----------+----------+---------+-----------+-------------+
| | |Remote Control | Low | Low |Ultra-low| N/A | High |
| | +--------------------+----------+----------+---------+-----------+-------------+
| | |AGV Control |Low~High |Low~Medium| N/A | N/A | Ultra-high |
| | +--------------------+----------+----------+---------+-----------+-------------+
| | |AR Assistance | Low | Low |Ultra-low| N/A | High |
+---+------------+--------------------+----------+----------+---------+-----------+-------------+
| 2 |High |Cloud VR and AR |Medium | Low | N/A | Ultra-low | N/A |
| |Experience | | ~High | | | | |
| |Video | | | | | | |
| | +--------------------+----------+----------+---------+-----------+-------------+
| | |Cloud Games | Low | High | N/A | N/A | N/A |
| | +--------------------+----------+----------+---------+-----------+-------------+
| | |Cloud Live Streaming| Medium | High | N/A | N/A | Medium |
+---+------------+--------------------+----------+----------+---------+-----------+-------------+
| 3 |Intelligent |Scientific Research |Ultra-high| Low | N/A | Ultra-low | Ultra-high |
| |Computing | | | | | | |
| | +--------------------+----------+----------+---------+-----------+-------------+
| | |Autonomous Vehicles |Ultra-high| Low | N/A | Ultra-low | Ultra-high |
+---+------------+--------------------+----------+----------+---------+-----------+-------------+
Figure 9: Characteristics of Typical Applications
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Since the DetNet applications differ in their requirements, it
demands specific desired behavior and different services requires
differentiated DetNet QoS. The classification of the deterministic
flows within different levels should be taken into considerations.
It is required to provide Latency, bounded jitter and packet loss
dynamically and flexibly in all scenarios for each characterized
flow. For example, as the figure shows, the services can be
classified into 4 types and DetNet applications and related
deterministic behaviors are differentiated within each type.
+--------------+---------+--------------+---------------+----------+
|Classification| 1 | 2 | 3 | 4 |
+--------------+---------+--------------+---------------+----------+
|Deterministic |Low |Low delay and |Low delay and | Ultra-low|
|Forwarding |delay |high bandwidth|Low packet loss| delay |
|Behaviors | | | |and jitter|
+--------------+---------+--------------+---------------+----------+
|Applications |Machine |Cloud |Autonomous |Remote |
|Examples |Vision |AR/VR |Vehicles |Control |
+--------------+---------+--------------+---------------+----------+
Figure 10: Classification of Deterministic Behaviors
5. Security Considerations
Security considerations for DetNet are covered in the DetNet
Architecture [RFC8655] and DetNet use cases [RFC8578] and DetNet
security considerations [RFC9055].
6. IANA Considerations
This document makes no requests for IANA action.
7. Acknowledgements
The authors would like to acknowledge Aihua Liu and Bin Tan for their
thorough review and very helpful comments.
8. References
8.1. Normative References
[I-D.ietf-detnet-scaling-requirements]
Liu, P., Li, Y., Eckert, T. T., Xiong, Q., Ryoo, J.,
zhushiyin, and X. Geng, "Requirements for Scaling
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Deterministic Networks", Work in Progress, Internet-Draft,
draft-ietf-detnet-scaling-requirements-06, 22 May 2024,
<https://datatracker.ietf.org/doc/html/draft-ietf-detnet-
scaling-requirements-06>.
[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>.
[RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
May 2017, <https://www.rfc-editor.org/info/rfc8174>.
[RFC8578] Grossman, E., Ed., "Deterministic Networking Use Cases",
RFC 8578, DOI 10.17487/RFC8578, May 2019,
<https://www.rfc-editor.org/info/rfc8578>.
[RFC8655] Finn, N., Thubert, P., Varga, B., and J. Farkas,
"Deterministic Networking Architecture", RFC 8655,
DOI 10.17487/RFC8655, October 2019,
<https://www.rfc-editor.org/info/rfc8655>.
[RFC8664] Sivabalan, S., Filsfils, C., Tantsura, J., Henderickx, W.,
and J. Hardwick, "Path Computation Element Communication
Protocol (PCEP) Extensions for Segment Routing", RFC 8664,
DOI 10.17487/RFC8664, December 2019,
<https://www.rfc-editor.org/info/rfc8664>.
[RFC9055] Grossman, E., Ed., Mizrahi, T., and A. Hacker,
"Deterministic Networking (DetNet) Security
Considerations", RFC 9055, DOI 10.17487/RFC9055, June
2021, <https://www.rfc-editor.org/info/rfc9055>.
[RFC9320] Finn, N., Le Boudec, J.-Y., Mohammadpour, E., Zhang, J.,
and B. Varga, "Deterministic Networking (DetNet) Bounded
Latency", RFC 9320, DOI 10.17487/RFC9320, November 2022,
<https://www.rfc-editor.org/info/rfc9320>.
Authors' Addresses
Junfeng Zhao
CAICT
China
Email: zhaojunfeng@caict.ac.cn
Zhao, et al. Expires 21 April 2025 [Page 15]
Internet-Draft Enhanced Use Cases for Scaling Determini October 2024
Quan Xiong
ZTE Corporation
China
Email: xiong.quan@zte.com.cn
Zongpeng Du
China Mobile
China
Email: duzongpeng@chinamobile.com
Zhao, et al. Expires 21 April 2025 [Page 16]