This project (in collaboration with Robert Beverly, Naval Postgraduate School) seeks to characterize the status of IPv6 deployment while simultaneously advancing the state-of-the-art in network measurement science and technology.
Funding source: NSF CNS-1111449. Period of performance: May 1, 2012 - April 30, 2016.
The impending exhaustion of available IPv4 address space is exerting exogenous pressure on network operators to transition to IPv6. As it pertains to network researchers, architects, and policy makers, there are two possible outcomes from this transition. IPv6 may be widely adopted and embraced, causing many existing methods to measure and monitor the Internet to be ineffective. In this transition scenario, the Internet will be even less well understood, and data even more scarce, than the existing, poorly instrumented IPv4-based network. A second possibility is that IPv6 languishes, transition mechanisms fail, or performance suffers. Either scenario demands new research on rigorous large-scale IPv6 measurement to inform technical, business, and policy decisions.
IPv6 Internet measurement research is in its infancy with little prior work. The two main lessons we can glean from the scant data available are: (i) architectural transitions - even those deemed minor but essential - are slow; (ii) the U.S. is behind other regions of the world in IPv6 deployment, and has not thus far invested in shedding quantitative light on this problem, despite making attempts to lightly nudge the market toward wider IPv6 adoption.
In this project, we will improve the fidelity, scope, and usability of IPv6 measurement technology. Building on our recent work, we will design measurement primitives for adaptive and intelligent probing, crucial to the efficiency needed for IPv6-scale topology measurement. We will also build tools to measure the characteristics of IPv6 adoption at the edge and compare characteristics of IPv4 and IPv6 connectivity. The resulting data sets will serve as input to our next task when we correlate these observations with other technical and socioeconomic data: address allocation, available geographic and traffic data, ISP organizational structure (commercial, government, educational), and political/regulatory factors influencing IPv6 deployment. Our final task is to improve the state of quantitative modeling of the IPv6 transition by gathering rigorous empirical data on the extent and effectiveness of converter technologies, investigating prevailing concerns over IPv6 performance and path inflation, and analyzing actual IPv6 traffic workloads on a major U.S. backbone.
The results of this project will provide solid empirically grounded understanding of the most difficult architectural transition ever attempted on the Internet, while simultaneously advancing the state-of-the-art in network measurement science and technology. A rigorous approach to the study of IPv6 deployment will represent a compelling case study for the current Internet, with applicability to technology transfer challenges in other domains.
The main parallel tasks of this proposal are: (1) characterization of observable IPv6 topology; (2) correlating the rate of IPv6 deployment with socioeconomic factors; and (3) quantitative assessment of IPv6 performance, based on new approaches to measuring the impact of transition technologies and workload characteristics.
The schedule of work below shows anticipated per-year progress in each task.
|Task 1: Provide a comprehensive view of the IPv6 topology from core to edge|
|1.1||Implement and test IPv6-specific topology probing algorithms using Ark measurement infrastructure||Year 1||Done|
|1.2||Extend our DNS lookup and database software to support IPv6 reverse DNS lookups||Year 1||Done|
|1.3||Collect IPv6 topology data||every year||Ongoing|
|1.4||Refine measurement methodologies||every year||Ongoing|
|1.5||Investigate possible approaches to alias resolution in the IPv6 space||Year 2||Done|
|1.6||Investigate methodologies to automate creation of AS links files from IPv6 topology data||Year 2||Done|
|1.7||Develop software to infer AS relationships in the IPv6 address space||Year 3||Done|
|1.8||Carry out comparative analysis of topological characteristics of IPv4 and IPv6 AS-core graphs||Year 3||Done|
|1.9||Analyze the observed evolution of the IPv6 AS-level graph||Year 3|
|Task 2: Correlate the rate of IPv6 deployment with socioeconomic parameters|
|2.1||Develop tools to automate data analysis and visualization of IPv4 and IPv6 allocation status||Year 1|
|2.2||Analyze publicly available routing announcement data||Year 2||Done|
|2.3||Compare IPv4 and IPv6 routing announcement patterns||Year 2||Done|
|2.4||Create a taxonomy of ASes requesting IPv6 addresses||Year 2|
|2.5||Analyze and validate of data on geographic penetration of IPv6 by countries and global regions of the world||Year 3||Done|
|2.6||(joint with RIPE) Analyze geographic characteristics of IPv6-capable clients querying root servers||every year||Done|
|2.7||(joint with RIPE) Correlate the trends observed at root servers with geopolitical and demographic data||every year||Done|
|Task 3: Conduct quantitative assessment of IPv6 performance, including the impact of transition technologies and workload characteristics|
|3.1||Compare and track performance to dual-stacked servers with both IPv4 and IPv6 support||Year 1||Done|
|3.2||(joint with RIPE) Measure and analyze the deployment and performance of IPv4/IPv6 converter mechanisms||Year 1 and 2|
|3.3||Study the TCP-level behavior of IPv6||Year 2 and 3|
|3.4||Investigate the prevalence and performance impact of middleboxes||Year 2 and 3||Done|
|3.5||Analyze actual IPv6 traffic workload on a major U.S. backbone||Year 2 and 3||Done|