Measuring IPv6 adoption

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

Why Study IPv6 Adop3on Now?

SIGCOMM’14 Measuring IPv6 Adop=on – Czyz et al. 2

(Image source: Geoff Huston, hAp://www.potaroo.net/tools/ipv4)

•  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

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


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


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 adop

3on” = lev

el rela3ve

to IPv4

METRICS (PREREQUISITE)


Prefix Alloca3on

0

200

400

600

800

1000

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 0

0.1

0.2

0.3

0.4

0.5

0.6

Mon

thly

Pre

fix A

lloca

tions

Rat

io IP

v6/IP

v4

IPv4IPv6

Ratio

Measuring IPv6 Adop=on – Czyz et al. 7 SIGCOMM’14 IANA

Exhaus=on

Naming: Domains & Record Types

0

0.2

0.4

0.6

0.8

1

v4 v6 v4 v6 v4 v6 v4 v6 v4 v6

Frac

tion

of A

ll D

NS

Que

ries

2011ï06ï08 2012ï02ï23 2012ï08ï28 2013ï02ï26 2013ï12ï23

other ANYTXTNSDSMXAAAA A

Measuring IPv6 Adop=on – Czyz et al. 8 SIGCOMM’14

More Similar (p < 0.05)

•  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:

Server Readiness: Alexa Top Domain Reachability

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

2011-06 2011-12 2012-06 2012-12 2013-06 2013-12

Frac

tion

of A

lexa

Top

10K

AAAA LookupsReachability


IPv6 World Day IPv6 Launch Day

Client Readiness: visitors to google.com

0

0.005

0.01

0.015

0.02

0.025

2009 2010 2011 2012 2013 2014

Frac

tion

Clie

nts

Usi

ng IP

v6


(Data method in Colir et al., 2010)

+151%

+147%

+61% -‐7% +43%

METRICS (OPERATIONAL)


Global Traffic

10M

100M

1G

10G

100G

1T

2010 2011 2012 2013 2014 0.0001

0.001

0.01

Traf

fic V

olum

e/C

usto

mer

(bps

)

Rat

io IP

v6/IP

v4

0.0064

IPv4 A (peak)IPv6 A (peak)

Ratio A (peaks)

IPv4 B (average)IPv6 B (average)

Ratio B (averages)


•  Arbor Networks global provider neslow data •  260 service providers (Dataset B) ~ 1/3 – 1/2 of all inter-‐AS traffic

+433% +470%

Applica3on Mix (% of IPv6)


{ User content

IPv6 Transi3on Technologies (Teredo + 6to4)

0

0.2

0.4

0.6

0.8

1

2009 2010 2011 2012 2013 2014

Frac

tion

of n

on-n

ativ

e IP

v6

Internet Traffic AInternet Traffic B

Google Clients


Mostly Transi3on

Mostly Na3ve

CONCLUSIONS


Conclusion 1: Regions Differ

1e-05

0.0001

0.001

0.01

0.1

1

Address(A1) Routing(T1) Traffic(U1)

AFRINICAPNIC

ARINLACNIC

RIPENCC


IPv6 / IPv4 Ra=

o

} Large Inter-‐Region Differences

Large Intra-‐Region (Cross-‐Metric) Differences

E.g. ARIN last place in alloca3on, first in traffic.

Conclusion 2: Perspec3ve Magers


0.0001

0.001

0.01

0.1

1

2009 2010 2011 2012 2013 2014 0.0001

0.001

0.01

0.1

1

IPv6

/ IP

v4 R

atio

A1 (allocation - monthly)

A1 (allocation - cumulative)

A2 (advertisement)

R2 (Google clients)

U1 (traffic - A.peaks)

U1 (traffic - B.averages)

N1 (.com NS)

T1 (topology)

P1 (performance)

2-‐3 order of magnitude difference

Conclusion 3: IPv6 is Real!


ß 20x growth!

ß 15x growth!

ß Traffic Flipped

ß Nearly on-‐par

Thank You!

Ques=ons?


BACKUP SLIDES


Internet Devices and Users Con3nue to Increase


Dataset Summary


/day /day

Prefix Adver3sement

100

1K

10K

100K

1M

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20140.0001

0.001

0.01

0.1

Pref

ix A

dver

tisem

ents

Rat

io IP

v6/IP

v4

IPv4IPv6

Ratio


AS Centrality

0

2

4

6

8

10

12

14

16

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

K-co

re d

egre

e

Dual-StackIPv6-Only

IPv4


DNS: .com & .net Zones

10

100

1K

10K

100K

1M

2007 2008 2009 2010 2011 2012 2013 2014 1e-05

0.0001

0.001

0.01

Rec

ords

in T

LD z

ones

Rat

io IP

v6/IP

v4 (.

com

)

.com A glue.net A glue

.net AAAA glue.com AAAA glueRatio .com glue

Ratio .net all probed (H.E.)Ratio .com all probed (H.E.)


IPv4 .com/.net TLD A and AAAA Query Rank Correla3on (Spearman’s ρ)


Within type: Strong Across type: Weak

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


Performance (using 10-‐ and 20-‐hop RTT)

0

100

200

300

400

500

2009 2010 2011 2012 2013 2014 0.5

0.6

0.7

0.8

0.9

1

Med

ian

RTT

(ms)

Rat

io IP

v6/IP

v4 p

erfo

rman

ce

IPv6 - Hop 20IPv4 - Hop 20IPv6 - Hop 10IPv4 - Hop 10

Ratio - Hop 10


Projec3ons

0.0001

0.001

0.01

0.1

1

2011 2012 2013 2014 2015 2016 2017 2018 2019

IPv6

/IPv4

A1 (allocation - cumulative)

U1 (traffic - A.peaks)

Polynomial Proj. (A1:R2 = 0.996; U1:R2 = 0.838)Exponential Proj. (A1:R2 = 0.984; U1:R2 = 0.892)


Measuring IPv6 adoption

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