IPv6 Network Deployment Monitoring and Analysis
draft-pang-v6ops-ipv6-monitoring-deployment-01
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| Last updated | 2025-07-04 (Latest revision 2025-03-03) | ||
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draft-pang-v6ops-ipv6-monitoring-deployment-01
v6ops R. Pang, Ed.
Internet-Draft J. Zhao, Ed.
Intended status: Standards Track China Unicom
Expires: 5 January 2026 M. Jin, Ed.
Huawei
S. Zhang, Ed.
China Unicom
4 July 2025
IPv6 Network Deployment Monitoring and Analysis
draft-pang-v6ops-ipv6-monitoring-deployment-01
Abstract
This document presents an IPv6 network end-to-end monitoring and
analysis system. It describes a standardized end-to-end monitoring
and analysis architecture and an indicator system, while also
enabling capabilities for end-to-end monitoring data collection and
integrated intelligent analysis. This solution has been verified in
the operators' network.
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 5 January 2026.
Copyright Notice
Copyright (c) 2025 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
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
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and restrictions with respect to this document. Code Components
extracted from this document must include Revised BSD License text as
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provided without warranty as described in the Revised BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Current IPv6 Deployment Status . . . . . . . . . . . . . 3
1.2. Current Approaches to Monitoring IPv6 Deployment . . . . 3
2. Problem Statement . . . . . . . . . . . . . . . . . . . . . . 4
2.1. Fragmented Monitoring Coverage . . . . . . . . . . . . . 4
2.2. Single-Dimensional Evaluation . . . . . . . . . . . . . . 4
2.3. Lack of Cross-Domain Correlation . . . . . . . . . . . . 4
2.4. Insufficient In-Depth Analysis . . . . . . . . . . . . . 4
2.5. Limited Dynamic Prediction . . . . . . . . . . . . . . . 4
3. IPv6 Network End-to-End Monitoring and Analysis System . . . 4
3.1. IPv6 Network End-to-End Monitoring and Analysis System
Architecture . . . . . . . . . . . . . . . . . . . . . . 5
3.1.1. Data Collection Layer . . . . . . . . . . . . . . . . 5
3.1.2. Intelligent Analysis Layer . . . . . . . . . . . . . 6
3.1.3. Visualization Layer . . . . . . . . . . . . . . . . . 7
3.2. Indicator System . . . . . . . . . . . . . . . . . . . . 7
4. Scenario-Based Capability Examples . . . . . . . . . . . . . 8
4.1. IPv6 Monitoring and Analysis on the User Side . . . . . . 8
4.2. IPv6 Support and Application Access Quality Monitoring for
Application Systems . . . . . . . . . . . . . . . . . . . 9
5. Use cases . . . . . . . . . . . . . . . . . . . . . . . . . . 9
5.1. User Network Quality Issue Localization . . . . . . . . . 9
5.2. Home terminals and router Traffic Analysis . . . . . . . 10
6. Security Considerations . . . . . . . . . . . . . . . . . . . 10
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 10
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.1. Normative References . . . . . . . . . . . . . . . . . . 10
8.2. Informative References . . . . . . . . . . . . . . . . . 10
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 11
1. Introduction
The emergence of IPv6 can be traced back to the 1990s, when the
development of IPv6 was initiated by the Internet Engineering Task
Force (IETF) to solve the problem of IPv4 address exhaustion. In
1998, the IPv6 protocol specification was published. As IPv6
adoption accelerating over the past years, the IPv6 protocol was
elevated to be an Internet Standard status [RFC8200] in 2017.
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1.1. Current IPv6 Deployment Status
In today's digital age, the deployment of IPv6 has become a core
driving force for network development. With the continuous expansion
of network scale and the emergence of new applications, the extensive
address space, enhanced security, and improved network performance of
IPv6 have made it a key element in network evolution. How to better
deploy and promote IPv6 networks has become a widely concerned issue.
As of 2023, significant strides have been made in the global
deployment of IPv6. According to the statistics from the 'Global
IPv6 Development Report 2024', in 2023 the deployment of IPv6
networks significantly accelerated, breaking through the 30% mark in
global coverage for the first time. Among leading countries, the
IPv6 coverage rate has reached or approached 70%, and the percentage
of IPv6 mobile traffic has surpassed that of IPv4.
[RFC9386] presents the state of IPv6 network deployment in 2022, and
its Section 5 lists common challenges, such as transition mechanisms,
network management and operation, performance, and customer
experience. 'ETSI-GR-IPE-001' also discusses the existing gaps in
IPv6-related use cases.
1.2. Current Approaches to Monitoring IPv6 Deployment
Existing IPv6 deployment monitoring approaches include (not an
exhaustive list):
* Internet Society Pulse: Curating information about levels of IPv6
adoption in countries and networks around the world.
* Akamai IPv6 Adoption Visualization: Reviewing IPv6 adoption trends
at a country or network level.
* APNIC IPv6 Measurement: Providing an interactive map that users
can click on to see the IPv6 deployment rate in a particular
country.
* Cloudflare IPv6 Adoption Trends: Offering insights into IPv6
adoption across the Internet.
* Cisco 6lab IPv6: Displaying IPv6 prefix data.
* Regional or National Monitoring Platforms: Examples include the NZ
IPv6, the RIPE NCC IPv6 Statistics, and the USG IPv6 & DNSSEC
External Service Deployment Status, among others.
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The aforementioned tools are capable of providing effective
statistics and visualization of IPv6 support levels. However, they
do not adequately address the key problems that currently exist. The
specific deficiencies are presented in the following five aspects.
2. Problem Statement
2.1. Fragmented Monitoring Coverage
Existing monitoring points are concentrated in the backbone network
[RFC7707], lacking fine-grained coverage of terminals and
applications.
2.2. Single-Dimensional Evaluation
It mainly relies on basic indicators such as connection availability
[RFC9099] and address allocation rate, lacking a comprehensive
assessment of service continuity, transmission quality, Network
Element Readiness, Active IPv6 Connections, and other key metrics.
2.3. Lack of Cross-Domain Correlation
The monitoring data of each network domain is isolated, making it
impossible to conduct correlation analysis of end-to-end traffic
paths [RFC9312].
2.4. Insufficient In-Depth Analysis
For instance, the IPv6 transformation in some private network
applications is not thorough enough, with internal application
systems yet to be upgraded. This results in secondary and tertiary
links, as well as multimedia content traffic, still relying
predominantly on IPv4. However, there is a lack of effective deep
monitoring methods to oversee these connections.
2.5. Limited Dynamic Prediction
Existing models find it difficult to quantify the impact of external
factors such as policies and regulations, user behavior patterns, and
market dynamics on the evolution of IPv6.
3. IPv6 Network End-to-End Monitoring and Analysis System
This system adheres to the following core principles.
* Correlation analysis: Capabilities for cross-domain data
integration and analysis
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* Business orientation: A standardized indicator measurement system
* Visualized operation: Key operations supported by visual charts
* Scalability: Full utilization of current infrastructure, support
for external system docking, and compatibility with multi-vendor
devices and subsystems
3.1. IPv6 Network End-to-End Monitoring and Analysis System
Architecture
+==================================================================+
| Visualization Layer |
+==================================================================+
| | | |
+==================================================================+
| Intelligent Analysis Layer |
+==================================================================+
| | | |
+==================================================================+
| Data Collection Layer |
+==================================================================+
| | | |
+----------------+ +----------------+ +----------------+ +----------------+
| Home Broadband | | Mobile | | IP Bearer | | Application |
| Network | | Network | | Network | | |
+----------------+ +----------------+ +----------------+ +----------------+
Figure 1: IPv6 Network End to End Monitoring and Analysis System
The system architecture is divided into three layers from top to
bottom (shown in Figure 1): the Data Collection Layer, the
Intelligent Analysis Layer, and the Visualization Layer.
Based on network functions and service scenarios, the network is
divided into four major professional network domains. These
specifically include: Home Broadband Network, Mobile Network, IP
Bearer Network, and Application.
3.1.1. Data Collection Layer
For these four major professional network domains, data cleaning,
transformation, and standardization are performed respectively.
Based on multi-source data fusion methods, the aggregation,
correlation and integration of data from each professional network
are realized, forming a unified data analysis foundation. According
to the hierarchical division of the network architecture, the
collected data indicators are explained from three dimensions: the
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user side, the network side and the application side. The core
collection indicators are specified as follows. For specific
indicator details, refer to Section 3.2.
* User side: network element readiness, network readiness, basic
resources, network traffic, active connections.
* Network side: network element readiness, network readiness, basic
resources, network traffic, active connections.
* Application side: network element readiness, network readiness,
basic resources, network traffic, active connections. Data
collection relies on the existing technical system. The specific
methods are:
- Adopt the established standardized data collection mechanism to
ensure the uniformity of data formats.
- Access the existing network management systems of each
professional network, and realize automatic collection and
synchronization of indicator data through interface docking.
TBD.
3.1.2. Intelligent Analysis Layer
The system develops a fine-grained, multi-dimensional traffic
analysis model. It enables correlated analysis of monitoring data
from cloud, network, edge, and end systems. This allows accurate
identification of issues related to IPv6 traffic improvement.
3.1.2.1. Multi-domain Traffic Correlation Analysis
* End-to-end cross-system integration: Integrate end-to-end data
from professional systems such as user home networks, access
networks, metro networks, IDCs, and content providers (covering
cloud, network, edge, and end). This enables end-to-end traffic
analysis, quality localization and demarcation, and evaluation of
overall IPv6 support.
* End-to-end traffic analysis: Perform correlated analysis on
traffic data from end, network, and cloud systems. It precisely
attributes the causes of IPv6 traffic changes to end, network, or
cloud subsystems.
- Network traffic analysis: Support collection of IPv6/IPv4
inbound and outbound traffic at key network nodes. Analyze
traffic change trends.
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- Application traffic analysis: Support collection and analysis
of IPv6/IPv4 active applications on the user side and
application side. Calculate IPv6 traffic data for different
service applications.
- Inter-network traffic analysis: Support analysis of IPv6/IPv4
traffic direction and application bearing information between
municipal-level networks. Provide an inter-municipal traffic
matrix.
* Dynamic traffic attribution
- Identify traffic-restricted areas. Develop multi-dimensional
problem investigation plans covering the network side, user
side, and application side. Investigate potential influencing
factors level by level. Attribute traffic fluctuations to
specific subsystems.
3.1.2.2. Quality Deterioration Delimitation and Topology Restoration
* User-level Topology Reconstruction: Using user services as the
link, reconstruct the end-to-end topology and diagnose latency/
packet loss segment by segment (e.g., segmental quality of home
terminal, access network, and application sides).
* Segmented Quality Degradation Localization: Compare IPv4/IPv6
performance differences segment by segment to locate degraded
network elements.
3.1.3. Visualization Layer
3.1.3.1. Indicator-Based Presentation
Data is statistically aggregated and presented according to
scenarios, with support for manual editing of display content and
dimensions.
3.1.3.2. Decision Support
3.2. Indicator System
Based on a standardized indicator system, conduct IPv6 support
monitoring and analysis for each professional domain, breaking down
monitoring metrics into specific services and network segments.
* Readiness Indicators
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- Network Element Readiness: IPv6 Readiness of Network Equipment,
End-User Devices, and Security Devices.
- Application Readiness: IPv6 Support Rate of Website
Applications and Business Systems.
- Infrastructure Readiness: IPv6 Readiness of Fixed Internet,
Mobile Internet, Private Lines, and Data Center Network (DCN)
Infrastructure.
- Network Readiness:
o IPv6 Network Coverage of Backbone Networks, Metropolitan
Area Networks (MANs), Internet Data Centers (IDCs), and
Private Lines.
o End-to-End IPv6 Network Performance of Backbone Networks,
Metropolitan Area Networks (MANs), Internet Data Centers
(IDCs), Private Lines, and Access Networks.
- Cloud Readiness: IPv6 Readiness of Content Delivery Networks
(CDNs), Cloud Services, Cloud Platforms, and DNS Servers.
* Operational Metrics
- IPv6 Traffic: IPv6 Traffic Share in Cross-Border, Inter-Domain,
Intra-Domain, Fixed Metropolitan Area Networks (MANs), Mobile
Core Networks, Internet Data Centers (IDCs), Private Lines, and
Applications.
- Active IPv6 Connections: Active IPv6 Connection Share in Fixed
Metropolitan Area Networks (MANs), Mobile Core Networks,
Internet Data Centers (IDCs), Private Lines, and Applications.
* Policy Compliance Indicators.
4. Scenario-Based Capability Examples
4.1. IPv6 Monitoring and Analysis on the User Side
Monitor and analyze data from fixed and mobile network user sides,
including: IPv6 support monitoring and IPv6 traffic quality analysis.
Support end-to-end data analysis at the intelligent analysis layer.
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4.2. IPv6 Support and Application Access Quality Monitoring for
Application Systems
Through application monitoring points, monitor and analyze the IPv6
support of application systems, including: website and APP
monitoring, IPv6 application access quality evaluation, and DNS
resolution capability monitoring.
TBD.
5. Use cases
5.1. User Network Quality Issue Localization
When User A experiences network congestion while playing cloud-based
games at home, it affects the gaming experience. To identify the
cause, it is necessary to collect performance data from each network
segment for quality localization. However, current independent
management of network domains prevents direct data correlation. The
network segments are as follows: N1 (terminal device to ONT), N2 (ONT
to BRAS), and N3 (BRAS to application side).
+-----------------+ +--------------+ +----------------+ +--------------+
| Terminal device |--------| ONT |--------| BRAS |--------| APP |
+-----------------+ +--------------+ +----------------+ +--------------+
| | | |
|<--------- N1 ----------> | | |
| |<--------- N2 ---------->| |
| | |<--------- N3 ---------->|
Figure 2: Network schematic diagram based on home broadband
network access application
The system detected end-to-end quality degradation of a certain
service. After the system segmented and delimited the quality
degradation, it compared the performance of N1/N2/N3 segment by
segment based on its preset multi-segment monitoring model
(Figure 2). It was determined that an abnormality occurred in the N3
network segment. At the same time, by correlating with CDN
scheduling logs, a content source switching event was found. The
original service node was a local IDC, while the monitored service
node was a remote node across provinces. Therefore, it is concluded
that the end-to-end quality degradation is caused by CDN remote
scheduling and the bottleneck of the N3 cross-network link.
Adjusting the CDN scheduling strategy can improve the quality
degradation issue.
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5.2. Home terminals and router Traffic Analysis
Home terminals and routers, as the "last kilometer" for users to
access the Internet, play a crucial role in user experience with
regard to their IPv6 support. The system detected that the
proportion of IPv6 traffic in a demonstration community was lower
than the city-wide average. By correlating with home broadband
terminal data, it was found that the proportion of bridge-mode
optical modems in this community was relatively high, and the
proportion of old devices among the connected routers was higher than
the average. Therefore, the root cause was identified as inadequate
terminal support. Old routers only support IPv4/NAT mode, which
forces IPv6 traffic to be downgraded. Targeted terminal replacements
were carried out. Specifically, bridge-mode optical modems for
community users were upgraded to router-mode ones. This has led to a
significant increase in the proportion of IPv6 traffic.
6. Security Considerations
The monitoring system must implement:
* Role-based access control.
* Anonymization of user-specific data.
* Secure data transmission protocols.
* Integrity verification for collected metrics.
7. IANA Considerations
TBD.
8. References
8.1. Normative References
[RFC8200] Deering, S. and R. Hinden, "Internet Protocol, Version 6
(IPv6) Specification", STD 86, RFC 8200,
DOI 10.17487/RFC8200, July 2017,
<https://www.rfc-editor.org/info/rfc8200>.
8.2. Informative References
[RFC7707] Gont, F. and T. Chown, "Network Reconnaissance in IPv6
Networks", RFC 7707, DOI 10.17487/RFC7707, March 2016,
<https://www.rfc-editor.org/info/rfc7707>.
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[RFC9099] Vyncke, É., Chittimaneni, K., Kaeo, M., and E. Rey,
"Operational Security Considerations for IPv6 Networks",
RFC 9099, DOI 10.17487/RFC9099, August 2021,
<https://www.rfc-editor.org/info/rfc9099>.
[RFC9312] Kühlewind, M. and B. Trammell, "Manageability of the QUIC
Transport Protocol", RFC 9312, DOI 10.17487/RFC9312,
September 2022, <https://www.rfc-editor.org/info/rfc9312>.
[RFC9386] Fioccola, G., Volpato, P., Palet Martinez, J., Mishra, G.,
and C. Xie, "IPv6 Deployment Status", RFC 9386,
DOI 10.17487/RFC9386, April 2023,
<https://www.rfc-editor.org/info/rfc9386>.
Authors' Addresses
Ran Pang (editor)
China Unicom
Beijing
China
Email: pangran@chinaunicom.cn
Jing Zhao (editor)
China Unicom
Beijing
China
Email: zhaoj501@chinaunicom.cn
Mingshuang Jin (editor)
Huawei
Beijing
China
Email: jinmingshuang@huawei.com
Shuai Zhang (editor)
China Unicom
Beijing
China
Email: zhangs366@chinaunicom.cn
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