srv6ops X. Gu, Ed.
Internet-Draft X. Yi, Ed.
Intended status: Standards Track N. Zhang, Ed.
Expires: 4 September 2025 China Unicom
3 March 2025
Requirements and Deployments for High-Speed IoV based on SRv6
draft-gu-srv6ops-req-dep-iov-srv6-00
Abstract
This document proposes a deployment scheme for high-speed IoV by
utilizing CATS, IFIT, SRv6, and network slicing technologies.
Requirements and problems are discussed, and a deployment scheme is
described in detail.
Status of This Memo
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This Internet-Draft will expire on 4 September 2025.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Conventions and Definitions . . . . . . . . . . . . . . . . . 3
3. Requirements . . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Requirements of Applications Affecting Driving . . . . . 4
3.2. Requirements of Applications Unrelated to Driving . . . . 4
4. Problem Statement . . . . . . . . . . . . . . . . . . . . . . 4
4.1. Inability to Identify the Traffic of Different
Applications . . . . . . . . . . . . . . . . . . . . . . 4
4.2. Insufficient Coordination Between Computing and
Network . . . . . . . . . . . . . . . . . . . . . . . . . 5
5. Deployment Scheme for High-Speed IoV . . . . . . . . . . . . 5
5.1. SRv6 . . . . . . . . . . . . . . . . . . . . . . . . . . 6
5.2. Network Slicing . . . . . . . . . . . . . . . . . . . . . 6
5.3. CATS . . . . . . . . . . . . . . . . . . . . . . . . . . 7
5.4. IFIT . . . . . . . . . . . . . . . . . . . . . . . . . . 7
6. Security Considerations . . . . . . . . . . . . . . . . . . . 8
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 8
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 8
8.1. Normative References . . . . . . . . . . . . . . . . . . 8
8.2. Informative References . . . . . . . . . . . . . . . . . 8
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 9
1. Introduction
In high-speed Internet of Vehicles (IoV), vehicles are interconnected
with road infrastructure, people, cloud services, and other traffic
participants through network connections, enabling real-time data
interaction and sharing. With the rapid development of big data,
artificial intelligence, and communication technologies, the
applications of the IoV are no longer limited to in-vehicle
entertainment and navigation services. Innovative applications such
as autonomous driving, remote control, and vehicle-road cooperation
have emerged. These emerging business types impose more stringent
and flexible differentiated requirements on network capabilities.
The application types in the IoV are mainly divided into two
categories. One category consists of applications highly related to
driving, such as autonomous driving, remote control, and intelligent
driving services. These applications require extremely low latency
guarantees to avoid traffic safety accidents. The other category
includes applications unrelated to driving, such as voice
communication, streaming media, and other entertainment applications,
which do not demand extremely high network quality guarantees.
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If the traffic of these two types of services is not differentiated
in the network, it may lead to the unreasonable allocation of network
resources. Delay-sensitive services may experience delays, packet
loss, and other issues during data transmission, posing serious
security risks. At the same time, the burst data generated by delay-
sensitive services may preempt the network resources of entertainment
applications, affecting the user experience. In addition, when two
types of service traffic are mixed together, it is likely to cause
data accumulation at network nodes, resulting in network congestion
and a decline in overall network performance.
By using technologies such as Segment Routing IPv6 (SRv6), network
slicing, Computing-Aware Traffic Steering (CATS), and In-situ Flow
Information Telemetry (IFIT), the traffic of these two types of
applications can be differentiated. On the one hand, it can meet the
differentiated needs of various applications and provide rich network
services for applications. On the other hand, it can improve the
utilization rate of network resources and achieve the optimal
resource matching.
This document aims to present a solution for high-speed vehicular
network scenarios. By utilizing CATS, IFIT, SRv6, and network
slicing technologies, the solution distinguishes between two types of
traffic flows in vehicular networks. It provides precise service
guarantees tailored to different applications, achieving optimal
allocation of network resources. This approach not only enhances
user experience but also ensures vehicle safety in high-speed
networking environments.
2. Conventions and Definitions
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
"OPTIONAL" in this document are to be interpreted as described in BCP
14 [RFC2119] [RFC8174] when, and only when, they appear in all
capitals, as shown here. Abbreviations and definitions used in this
document:
*IoV: Internet of Vehicles.
*SRv6: Segment Routing IPv6.
*CATS: Computing-Aware Traffic Steering.
*IFIT: In-situ Flow Information Telemetry.
3. Requirements
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3.1. Requirements of Applications Affecting Driving
Applications related to driving, such as autonomous driving, remote
control, and intelligent driving, have extremely high requirements
for network quality.
--Vehicles need to make rapid decisions in response to changes in
road conditions. The network must provide extremely low latency
guarantees to ensure the safety and stability of vehicle driving.
--The implementation of these applications relies on a large amount
of sensor data, and the accuracy and integrity of the data directly
affect the decision-making and control of the vehicles. The network
needs to ensure the high reliability of data transmission to ensure
that vehicles can accurately perceive the surrounding environment
under various complex conditions.
--The network needs to have sufficient bandwidth to support the large
amount of sensor data generated during the operation of these
applications. Meanwhile, in collaborative scenarios, there is a need
for big data interaction between vehicles as well as between vehicles
and cloud servers. The network needs to have high bandwidth to
ensure the timeliness and integrity of information interaction.
--When driving at high speeds, the position of the vehicle changes
rapidly. The network should be able to switch routes quickly to
ensure that the vehicle maintains a stable connection with other
communication entities, so as to continuously obtain accurate
information.
3.2. Requirements of Applications Unrelated to Driving
Entertainment applications such as video downloading, online music
playback, and email do not affect driving and are non-delay-sensitive
applications. Therefore, these applications have a relatively low
priority in the IoV scenario and do not impose high requirements on
network quality.
4. Problem Statement
4.1. Inability to Identify the Traffic of Different Applications
The current network's inability to identify the traffic of different
applications will lead to the unreasonable allocation of network
resources, which seriously affects the overall performance of the IoV
and the user experience. On the one hand, for latency-sensitive
applications, low latency is a crucial factor in ensuring the
system's rapid response and accurate decision-making. Network
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congestion may be caused by the data generated by entertainment
applications, which in turn increases the latency. As a result,
vehicles are unable to make correct decisions in a timely manner, and
their safety cannot be guaranteed.On the other hand, although
entertainment applications have a relatively low priority, users
still expect to obtain smooth audio and video services or social
services. In an environment with mixed traffic, these applications
may be affected due to the network resources being preempted by
latency-sensitive applications, leading to problems such as audio and
video stuttering and delayed information sending, which will affect
the service experience.
4.2. Insufficient Coordination Between Computing and Network
Meanwhile, due to the insufficient coordination between computing and
networking in the current network, when calculating the routing path,
it often only focuses on factors at the network level while ignoring
the status of computing resources. Or it only pays attention to the
allocation of computing resources without taking the actual
transmission capacity of the network into account. This one-sided
routing calculation method makes the adaptation between the data
transmission path and the computing resources poor, and it is unable
to fully leverage the advantages of the integration of computing and
networking. As a result, business processing efficiency is
compromised, making it difficult to meet the increasingly diverse and
demanding requirements of modern services.
5. Deployment Scheme for High-Speed IoV
A vehicular network solution based on application-network
collaboration was deployed and validated for the first time in Hebei
Province, China. This solution integrates several advanced
technologies, including SRv6 [RFC9602]
[I-D.liu-srv6ops-problem-summary], network slicing, CATS [RFC9341]
[I-D.yi-cats-hierarchical-metric-distribution] and IFIT
[I-D.song-opsawg-ifit-framework]. By leveraging these technologies,
the solution provides a flexible resource allocation framework and
ensures high-quality network service guarantees for high-speed
vehicular networks by leveraging these technologies. This integrated
approach optimizes resource utilization while meeting the stringent
performance requirements of modern vehicular communication systems.
Figure 1 shows the architectural schematic of the deployment scheme.
+--------------------------------------+
+ -----| Computing and Network Controller |---------+
| +--------------------------------------+ |
| | | |
| | +-------------------- + | |
| | | +-----------------+ | | |
+-+ | | |Dedicated Channel| | | |
|V| | | +-----------------+ | | |
|e| +-------+ |（SRv6 Policy1 with | +-------+ +---------+
|h| |Network| | network slicing） | |Network| |Computing|
|i|--| |--| |--| |--| |
|c| |Device | | +-----------------+ | |Device | |Resource |
|l| +-------+ | | Shared Channel | | +-------+ +---------+
|e| | +-----------------+ |
+-+ |（SRv6 Policy2 with- |
| out network slicing |
+---------------------+
<--------------------------IFIT,CATS-------------------------->
Figure 1: Deployment-architecture
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5.1. SRv6
By leveraging SRv6 technology, network paths can be flexibly
configured and dynamically adjusted according to specific service
requirements, enabling precise traffic control and customized
routing.
The solution provides two types of channels for application traffic:
dedicated channels and shared channels. The dedicated channel
ensures high availability and can provide stable, efficient network
resources for critical applications in vehicular networks. In
contrast, the shared channel emulates the public channels in current
networks that lack quality-of-service guarantees, which may
experience congestion and packet loss during periods of high service
traffic.
Through the deployment of different SRv6 policies for various types
of business traffic, the network can deliver differentiated services,
providing dedicated assurance for key applications and enhancing
overall network performance. For mission-critical traffic related to
driving, the controller enforces SRv6 Policy1, directing it to
traverse the dedicated channel. For non-driving-related traffic,
such as media streams or file data streams, the controller applies
SRv6 Policy2, routing it through the shared channel. This approach
ensures optimal resource allocation while meeting diverse service
requirements.
5.2. Network Slicing
Network slicing technology enables customized configuration and
management according to different application scenarios and service
requirements, thereby providing differentiated quality of service.
For critical applications in vehicular networks, extremely high
levels of reliability and real-time performance are required.
Network slicing can isolate such high-priority services from ordinary
ones, creating a dedicated slice with high reliability and low
latency to ensure the accurate and timely transmission of control
commands, while avoiding interference from other types of traffic.
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In this solution, network slicing is implemented on the dedicated
channel to provide high-quality network service guarantees for
driving-related applications. Based on service requirements and
network conditions, slicing management policies are formulated and
distributed to all nodes within the network, ensuring that the slices
operate as intended. This approach optimizes resource allocation and
enhances the overall performance and reliability of the network for
mission-critical applications.
5.3. CATS
For latency-sensitive services, a distributed routing decision-making
model is adopted, where network devices perform routing decisions.
This approach enables rapid routing and fast switching, which is
critical for maintaining performance in time-critical applications.
For non-latency-sensitive services, a centralized routing decision-
making model is utilized, with routing decisions made by a
centralized controller. This model provides a global perspective,
allowing for higher resource utilization across the network.
In the hybrid solution, computational and networking factors are
independently distributed, avoiding large-scale modifications to
network devices. The choice between centralized and distributed
routing decision-making is made on an as-needed basis, providing
differentiated services tailored to specific business requirements.
This flexible approach ensures optimal performance and resource
allocation for diverse service types.
5.4. IFIT
The IFIT technology marks feature information by inserting an IFIT
header into real business packets, enabling real-time perception of
network traffic, topology structures, and device states. This high-
precision in-band detection capability allows the network to
dynamically sense the actual requirements of various application
flows, thereby providing differentiated services for different
applications and achieving rational network resource allocation.
Moreover, IFIT technology offers high-precision performance
monitoring and fault localization capabilities for key services in
vehicular networks.
In computing and network controller, relevant IFIT parameters can be
configured at each compute-capable routing gateway node participating
in the in-band detection process, enabling the in-band detection
function. At the same time, IFIT monitoring strategies are
distributed to these nodes. After a vehicle completes standard 5G
registration and successfully establishes an IPv6 session, it
initiates a service request. The gateway devices then report the in-
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band detection results, allowing performance metrics to be viewed.
This approach ensures efficient and precise monitoring of network
performance for vehicular services.
6. Security Considerations
TBD
7. IANA Considerations
TBD
8. References
8.1. 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>.
[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>.
[RFC9602] Krishnan, S., "Segment Routing over IPv6 (SRv6) Segment
Identifiers in the IPv6 Addressing Architecture",
RFC 9602, DOI 10.17487/RFC9602, October 2024,
<https://www.rfc-editor.org/info/rfc9602>.
[RFC9341] Fioccola, G., Ed., Cociglio, M., Mirsky, G., Mizrahi, T.,
and T. Zhou, "Alternate-Marking Method", RFC 9341,
DOI 10.17487/RFC9341, December 2022,
<https://www.rfc-editor.org/info/rfc9341>.
8.2. Informative References
[I-D.liu-srv6ops-problem-summary]
Liu, Y., Voyer, D., Graf, T., Miklos, Z., Contreras, L.
M., Leymann, N., Song, L., Matsushima, S., Xie, C., and X.
Yi, "SRv6 Deployment and Operation Problem Summary", Work
in Progress, Internet-Draft, draft-liu-srv6ops-problem-
summary-04, 11 February 2025,
<https://datatracker.ietf.org/doc/html/draft-liu-srv6ops-
problem-summary-04>.
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[I-D.yi-cats-hierarchical-metric-distribution]
Yi, X., Zhang, N., and H. Shi, "Hierarchical methods of
computing metrics distribution", Work in Progress,
Internet-Draft, draft-yi-cats-hierarchical-metric-
distribution-01, 16 October 2024,
<https://datatracker.ietf.org/doc/html/draft-yi-cats-
hierarchical-metric-distribution-01>.
[I-D.song-opsawg-ifit-framework]
Song, H., Qin, F., Chen, H., Jin, J., and J. Shin,
"Framework for In-situ Flow Information Telemetry", Work
in Progress, Internet-Draft, draft-song-opsawg-ifit-
framework-21, 23 October 2023,
<https://datatracker.ietf.org/doc/html/draft-song-opsawg-
ifit-framework-21>.
Authors' Addresses
Xinrui Gu (editor)
China Unicom
Beijing
China
Email: guxr12@chinaunicom.cn
Xinxin Yi (editor)
China Unicom
Beijing
China
Email: yixx3@chinaunicom.cn
Naihan Zhang (editor)
China Unicom
Beijing
China
Email: zhangnh12@chinaunicom.cn
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