Measuring IPv6 Adop3on
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1 Measuring IPv6 Adop3on Jakub Czyz, University of Michigan Mark Allman, Interna=onal Computer Science Ins=tute Jing Zhang, University of Michigan ScoA Iekel- Johnson, Arbor Networks Eric Osterweil, Verisign Labs Michael Bailey, University of Michigan and University of Illinois SIGCOMM 2014 Chicago, IL, USA August 17-22, 2014
2 Why Study IPv6 Adop3on Now? Internet con=nues growing IPv4 space shrinking IPv4 exhaus=on events: IANA: February 2011 Asia/Pacific: April 2011 Europe: September 2012 La=n America: June 2014 IPv6 Community Flag Days 2011 & 2012 Total Free IPv4 /8 At Registries IANA Exhaus=on (Image source: Geoff Huston, hap:// Measuring IPv6 Adop=on Czyz et al. 2
3 Our Study Goal: a systemic big picture of IPv6 adop=on Trading off depth for breadth Are there cross- perspec=ve insights? Mul3- perspec3ve: 10 datasets Mul3- year: 2-10 years Mul3- aspect: 12 metrics Findings: IPv6 adop3on varies by where you measure (region) varies by what you measure recently made a qualita=ve jump Measuring IPv6 Adop=on Czyz et al. 3
4 Data Analyzed Exis3ng/Public Datasets: RIR alloca=on Route Views BGP, RIPE- RIS BGP Google.com clients, Verisign zone files, CAIDA Ark RTT New Datasets: Traffic: Arbor Networks global traffic Naming: Verisign.com/.net queries via IPv4, via IPv6 Content: Tes=ng data of Alexa top- 10K sites Measuring IPv6 Adop=on Czyz et al. 4
5 Metrics Prerequisite IP Func3ons Address Alloca=on Address Adver=sement Topology DNS Name servers DNS Resolvers DNS Queries Server Readiness Client Readiness Opera3onal Characteris3cs Traffic Volume Applica=on Mix Transi=on Technologies Performance (RTT) IPv6 adop3on = level rela3ve to IPv4 Measuring IPv6 Adop=on Czyz et al. 5
6 METRICS (PREREQUISITE) Measuring IPv6 Adop=on Czyz et al. 6
7 Prefix Alloca3on Monthly Prefix Allocations IPv4 IPv6 Ratio Ratio IPv6/IPv IANA Exhaus=on Measuring IPv6 Adop=on Czyz et al. 7
8 Naming: Domains & Record Types Queries from.com/.net; IPv4 & IPv6 name servers Five day- long packet samples over 2.5 years IPv6 DNS users query similar domains as IPv4 Query types are converging over this =me period: Fraction of All DNS Queries More Similar (p < 0.05) other ANY TXT NS DS MX AAAA A 0 v4 v6 v4 v6 v4 v6 v4 v6 v4 v Measuring IPv6 Adop=on Czyz et al. 8
9 Server Readiness: Alexa Top Domain Reachability Fraction of Alexa Top 10K AAAA Lookups Reachability IPv6 World Day IPv6 Launch Day Measuring IPv6 Adop=on Czyz et al. 9
10 Client Readiness: visitors to google.com (Data method in Colir et al., 2010) Fraction Clients Using IPv % - 7% +61% +147% +151% Measuring IPv6 Adop=on Czyz et al. 10
11 METRICS (OPERATIONAL) Measuring IPv6 Adop=on Czyz et al. 11
12 Traffic Volume/Customer (bps) 1T 100G 10G 1G 100M Global Traffic Arbor Networks global provider neslow data 260 service providers (Dataset B) ~ 1/3 1/2 of all inter- AS traffic +470% +433% IPv4 A (peak) IPv4 B (average) 10M IPv6 A (peak) IPv6 B (average) Ratio A (peaks) Ratio B (averages) Ratio IPv6/IPv4 Measuring IPv6 Adop=on Czyz et al. 12
13 Applica3on Mix (% of IPv6) User content { Measuring IPv6 Adop=on Czyz et al. 13
14 IPv6 Transi3on Technologies (Teredo + 6to4) 1 Fraction of non-native IPv Mostly Transi3on Internet Traffic A Internet Traffic B Google Clients Mostly Na3ve Measuring IPv6 Adop=on Czyz et al. 14
15 CONCLUSIONS Measuring IPv6 Adop=on Czyz et al. 15
16 Conclusion 1: Regions Differ IPv6 / IPv4 Ra=o AFRINIC APNIC ARIN LACNIC RIPENCC } Large Inter- Region Differences 1e-05 Address(A1) Routing(T1) Traffic(U1) Large Intra- Region (Cross- Metric) Differences E.g. ARIN last place in alloca3on, first in traffic. Measuring IPv6 Adop=on Czyz et al. 16
17 Conclusion 2: Perspec3ve Magers 1 P1 (performance) 1 A1 (allocation - monthly) IPv6 / IPv4 Ratio A1 (allocation - cumulative) A2 (advertisement) T1 (topology) order of magnitude difference R2 (Google clients) U1 (traffic - B.averages) N1 (.com NS) U1 (traffic - A.peaks) Measuring IPv6 Adop=on Czyz et al. 17
18 Conclusion 3: IPv6 is Real! ß 20x growth! ß 15x growth! ß Traffic Flipped ß Nearly on- par Measuring IPv6 Adop=on Czyz et al. 18
19 Thank You! Ques=ons? Measuring IPv6 Adop=on Czyz et al. 19
20 BACKUP SLIDES Measuring IPv6 Adop=on Czyz et al. 20
21 Internet Devices and Users Con3nue to Increase Measuring IPv6 Adop=on Czyz et al. 21
22 Dataset Summary /day /day Measuring IPv6 Adop=on Czyz et al. 22
23 Prefix Adver3sement 1M 0.1 Prefix Advertisements 100K 10K 1K 100 IPv4 IPv6 Ratio Ratio IPv6/IPv Measuring IPv6 Adop=on Czyz et al. 23
24 AS Centrality Dual-Stack IPv6-Only IPv4 K-core degree Measuring IPv6 Adop=on Czyz et al. 24
25 DNS:.com &.net Zones Records in TLD zones 1M 100K 10K K.com A glue 100.net A glue.net AAAA glue.com AAAA glue Ratio.com glue Ratio.net all probed (H.E.) Ratio.com all probed (H.E.) 1e Ratio IPv6/IPv4 (.com) Measuring IPv6 Adop=on Czyz et al. 25
26 IPv4.com/.net TLD A and AAAA Query Rank Correla3on (Spearman s ρ) Within type: Strong Across type: Weak Measuring IPv6 Adop=on Czyz et al. 26
27 Naming: Domains Queries from.com/.net; IPv4 & IPv6 name servers Five day- long samples over 2.5 years Four sets of top 100k domains: For both IPv4 and IPv6 packets (user popula=ons) Within each, for domains queried by A and AAAA Finding: IPv4 to IPv6 popula=ons correlate strongly for the same query type {A,AAAA} e.g. Spearman s ρ of 0.7 for IPv4 A versus IPv6 A So, IPv6 DNS users query similar domains as IPv4 Measuring IPv6 Adop=on Czyz et al. 27
28 Performance (using 10- and 20- hop RTT) Median RTT (ms) IPv6 - Hop 20 IPv4 - Hop 20 IPv6 - Hop 10 IPv4 - Hop 10 Ratio - Hop Ratio IPv6/IPv4 performance Measuring IPv6 Adop=on Czyz et al. 28
29 Projec3ons 1 IPv6/IPv A1 (allocation - cumulative) U1 (traffic - A.peaks) Polynomial Proj. (A1:R 2 = 0.996; U1:R 2 = 0.838) Exponential Proj. (A1:R 2 = 0.984; U1:R 2 = 0.892) Measuring IPv6 Adop=on Czyz et al. 29
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