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Cell Spotting:Studying the Role of Cellular Networks
in the Internet
John RulaFabián E. Bustamante
Moritz Steiner*
*
✝*
✝✝
1
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Understanding cellular growth is critical
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• On subscriptions• >7.3 billion mobile phone subscriptions worldwide
• And content consumption• 3.1hr/day of digital media (1.4x as on
desktops/laptops)*• 50% of web traffic**• 91% of daily Facebook usage
Growing dominance of mobile
* eMarketer 4/17** Cisco VNI 2016
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• 4.2x more mobile broadband subscribers• Mobile traffic growing at 45% annually• A path to connect the other half of the world
Part of the growth is cellular
But how much? And where?
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Access TECHNOLOGY
✚Fastest growing tech
Mobile
⎼Hard to measure
CellularAccess DEVICE
✚Easy to measure: User-agent, device properties
Mobile
⎼Not a good proxy: >50% of mobile traffic is over WiFi
≈ Cellular
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• Can’t tell which traffic is cellular • Don’t know how cell networks are organized• Can’t see global usage trends
Understanding cellular growth
Challenges?
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• Approach to label cell networks and traffic• Validation with ground truth data• Detailed look at global cellular usage
Our work
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• Motivation• Approach• Validation• Findings
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Identify cellular IP addresses
• Detect network interface from browser API• Beacon data for cell networks identification• Requests to a large CDN as a proxy for traffic
Summary of our approach
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Network interface from browserNetwork Information API• Detect client’s network connectivity• Notify of connection changes• Measure recent RTT and T-put
Limitation: Only knows client’s network interface
ConnectionType: WiFi
Hotspot
ConnectionType: Cell
ConnectionType: WiFi
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From CDN Real User Monitoring (RUM) system• Network Information API available in 15% of beacons• 100s of millions of beacons per month
Calculate Cellular Ratio for each /24 and /48 CIDR• CR = (Cellular Hits) / (Cellular Hits + WiFi Hits)
Label subnets with Ratios > 0.5 as CELLULAR
Beacon data for cell identification
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Calculate demand across entire CDN platform
Demand Unit (DU): relative measure of all CDN HTTP requests (out of 100,000)
Platform data for cell demand
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• Motivation• Approach• Validation• Findings
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High precisionbut potential for false-negatives
Diverse operators for validation
Operator Precision Recall F1European [Mixed] 0.99 0.82 0.90US [Dedicated] 1.00 1.00 1.00Middle Eastern [Mixed] 0.98 0.98 0.98
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• Motivation• Approach• Validation• Findings
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Worldwide Cellular Subnets:Global cellular IP space
Number of /24 350,687Number of /48 23,230Active IPv4 7.3%Active IPv6 1.2%
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Global cellular IP space
Continent # /24 # /48 % Active IPv4 % Active IPv6Africa 79,091 28 53.2% 2%Asia 86,618 4,613 5.7% 0.5%Europe 65,442 2,117 4.8% 0.3%North America 27,595 16,166 2.1% 9.9%Oceania 4,352 35 5.4% 0.07%South America 87,589 271 22.6% 0.9%
Spread across 668 Cellular ASes.
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Global cellular IP space
Continent # /24 # /48 % Active IPv4 % Active IPv6Africa 79,091 28 53.2 2Asia 86,618 4,613 5.7 0.5Europe 65,442 2,117 4.8 0.3North America 27,595 16,166 2.1 9.9Oceania 4,352 35 5.4 0.07South America 87,589 271 22.6 0.9
49.2% of all IPv6 demand is cellular
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16.2% from cellular addresses end 2016
Global cellular demand
16.20%
83.80%
Cellular Fixed Line
3% 3% 4%
16%
35%
39%
OceaniaAfricaSouth AmericaEuropeNorth AmericaAsia
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From ~26% (Asia, Africa) to 12% in Europe
Cell fraction of demand by continent
0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%
Oceania
Africa
South America
Europe
North America
Asia Percentage of continent demand that is cellular:
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And by country
0.0 0.2 0.4 0.6 0.8 1.0CeOOuODU DemDnd RDtiR
10-2
10-1
100
101
102
103
104
1RUm
. C
eOOu
ODU
Dem
Dn
d x
10
0,0
00
1AE86AAFA62C
United States IndiaIndonesia
Ghana
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Top networks dominate demand
100 101 102
5DnNed A61 #
10-6
10-5
10-4
10-3
10-2
10-1
Cellu
lDr
Dem
Dn
d (
%)
Top 10 make up 38% of cellular demand
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Serve both cellular and fixed-line access networksKey networks are mixed
Cellular ASNs Cellular Demand
0ixed DedicDted0
10
20
30
40
50
60
70
DemDnd
0ixed DedicDted0
10
20
30
40
50
60
A61
Cou
nt
Majority of networks are
mixed
Majority of demand
comes from dedicated
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Mixed networks vary greatly
0 100 200 300 400 500 6005DnNed A61s
10−1
100
101
102
103
Dem
Dnd
(DU)
CellulDU)ixed
Cellular dominates some networks’ demand
Less so in other networks
Need prefix-level granularity for analysis
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Demand concentrated in few subnets
100 101 102 103 104
5Dnked /24 Subnet
10-5
10-4
10-3
10-2
10-1
100
101
Dem
Dn
d
CellulDrFixed
Top 30 account for 73% of cellular demand
Top 2,600 account for 73% of fixed demand
Similar patterns across all ASes
Top 3 account for 53% of cellular demand
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Most cellular clients share DNS resolvers
0.0 0.2 0.4 0.6 0.8 1.016 CellulDr FrDFtiRn
0.0
0.2
0.4
0.6
0.8
1.0
CD
F
ResRlver CellulDr FrDFtiRn
20% Fixed line
~20% Cellular60% Mixed
Most DNS resolvers shared with fixed line
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Public resolver usage higher outside US
U.S.
Brazil Vietnam
South Africa
India
Hong Kong
Nigeria
Algeria
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This work …• Accurate identification of cellular IP address space• Measure IP-level activity of cellular access• Cellular usage and behavior across different axes
Much to be done …• 19.7% cell demand increase last 8 months• Temporal dynamics of assignment• Sampling, …
Looking at the role of cellular
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Questions?
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Sept. 2016 launched India-wide 4G LTE“FREE, Unlimited Data for 6 months!”
Cellular Case Study: Reliance JioTech Capability, Deployment, Economics
0
5
10
15
20
25
30
35
40
Perc
ent C
ount
ry T
raffi
c (%
)
Pre-promotion, June 2016: Reliance carried 1.2% of India’s traffic
37.7% of India’s traffic by June 2017
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13.7% of Traffic is Cellular86.3% is Fixed Line
Country Comparison: France & Indonesia
Dem
and
(DU
)
ASN
Top 10 French ISPs
Cellular Traffic Fixed Line Traffic
!
Dem
and
(DU
)
ASN
Top 10 Indonesian ISPs
Cellular Traffic Fixed Line Traffic
66.8% of Traffic is Cellular33.2% is Fixed Line4 out of top 5 ISPs are majority cellular
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