| Internet-Draft | IPv6 Network Monitoring Deployment | March 2025 |
| Pang, et al. | Expires 4 September 2025 | [Page] |
This document proposes an IPv6 network end-to-end monitoring and analysis framework. The aim is to address key issues existing in current IPv6 deployment monitoring, such as limited coverage, insufficient depth of analysis, and lack of cross-domain collaboration.¶
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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. With IPv6 adoption accelerating over the past years, the IPv6 protocol was elevated to be a Internet Standard [RFC8200] in 2017.¶
This document proposes an IPv6 end-to-end monitoring and analysis framework. The aim is to address key issues existing in current IPv6 deployment monitoring, such as limited coverage, insufficient depth of analysis, and lack of cross-domain collaboration. Through defining standardized data collection interfaces, multi-dimensional quality assessment metrics, and cross-domain correlation analysis models, this framework enables the assessment of IPv6 deployment quality and problem location across the entire cloud-networ-edge-terminal link.¶
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 vast 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.¶
Although current analyses of insufficient IPv6 network deployment often focus on technical gaps, there is a lack of tools that can support end-to-end monitoring and analysis across clouds, networks, edges, and terminals from a practical network perspective. This gap makes it impossible to conduct multidimensional and fine-grained analyses of the shortcomings in IPv6 deployment.¶
For example, most network domains are currently managed independently, focusing only on the shortcomings and quality issues of IPv6 deployment within a single management domain. They are unable to directly analyze data correlation between domains, making it difficult to accurately locate network quality issues¶
Existing IPv6 deployment monitoring approaches include (Maybe not all are covered):¶
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.¶
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.¶
Existing monitoring points are concentrated in the backbone network [RFC7707], lacking fine-grained coverage of terminals and applications.¶
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, etc.¶
The monitoring data of each network domain is isolated, making it impossible to conduct correlation analysis of end-to-end traffic paths [RFC9312].¶
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 predominantly relying on IPv4. However, there is a lack of effective deep monitoring methods to oversee these connections.¶
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.¶
As a network operator, we specify an architectural framework for IPv6 end-to-end monitoring and analysis systems, defining a standardized methodology for cross-domain data correlation, multidimensional traffic analysis, and quality assessment across cloud-network-edge-device ecosystems.¶
The framework establishes key performance indicators (KPIs), monitoring interfaces, and analyzing procedures to address IPv6 deployment challenges in heterogeneous network environments.¶
This framework addresses these gaps through standardized data collection methods and multidimensional analysis techniques.¶
+-+-+-+-+-+-+-+-+-+-+-++-+-+-+-+-+-+-+-+-+-+
| Monitoring and Analysis platform |
+-+-+-+-+-+-+-+-+-+-+-++-+-+-+-+-+-+-+-+-+-+
|
------------->---------------------->----|----------<-----------------<---------
| | | |
| | | |
+-----------------+ +----------------+ +--------------------+ +--------------+
| Home Network |---------| Mobile Network |--------| IP bearer network |-------| Application |
+-----------------+ +----------------+ +--------------------+ +--------------+
The framework defines four critical domains. By connecting the monitoring subsystems in various fields of cloud, network, edge, and terminal, end-to-end data integration across multiple links can be achieved. * Home Network Domain: - Home gateway IPv6 capabilities - End-device Protocol Stack Status¶
Support multiple data collection methods (e.g., Kafka/ SFTP [RFC9132], NetFlow [RFC3954] /NetStream [RFC5130], telemetry [RFC9232]) with protocol-specific configurations. Additionally, if a real-time traffic collection method is required, the Deploy IPFIX exporters [RFC7011] at strategic nodes for flow data capture.¶
## User Network Quality Question Positioning 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
The end-to-end monitoring capabilities of the platform enable comprehensive data correlation and analysis, allowing for precise localization of issues and significantly enhancing the efficiency and effectiveness of network quality management. By leveraging an IPv6 end-to-end network monitoring and analysis platform, we collected latency and packet loss data from N1, N2, and N3 network segments. The platform applies a metric model to precisely identify quality issues. The analysis revealed that the congestion in the critical path of N3 was the root cause of the problem. Specifically, the CDN content scheduling was switched from a local server to a remote server, which resulted in the transmission path requiring cross-network scheduling. Due to the high latency and packet loss rate of the inter-network links, the end-to-end latency and packet loss rate increased significantly.¶
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. Take a popular video application as an example. It has a large number of users in both mobile and home network environments. Within the statistical time period, the proportion of IPv6 traffic generated by mobile network users in the application is much higher than that of home network users. After a systematic analysis from multiple dimensions including the user side, network side, and application side, it was found that the IPv6 support of home terminals is insufficient.¶
The monitoring system must implement: - Role-based access control - Anonymization of user-specific data - Secure data transmission protocols - Integrity verification for collected metrics¶
TBD.¶