ITU-T Kaleidoscope 2010
Beyond the Internet? - Innovations for
future networks and services
GEOHYBRID: A HIERARCHICAL
APPROACH FOR ACCURATE AND
SCALABLE GEOGRAPHIC
LOCALIZATION
Dr. Bamba Gueye
Joint work with Ibrahima Niang and Bassirou Kasse
University Cheikh Anta Diop of Dakar
bamba.gueye@ucad.edu.sn
http://edmi.ucad.sn/~gueye
Pune, India, 13 – 15 December 2010
Motivations
New class of location-aware applications
Web services: targeted advertising, locating
cyber-criminality, restricted content delivery
Location-based security check
Geographic information of the Internet
routes
Analyze the geographic behavior of network
routing, internet topology mapping
Optimization of the decision taking
process of a Grid Resource Broker
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Problem statement
IP-location mapping: Given the IP address of an
Internet host, can we estimate its geographic location?
AS1
AS2
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AS3
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How to locate Internet host ?
Passive measurements approach
Use databases and exhaustive tabulation
Ex: GeoBytes, GeoURL, GeoIP
Active measurements approach
Round-trip time-based or/and Traceroutebased
Ex: GeoPing, CBG, GeoBuD, GeoTrack,
SarangWorld project
Hybrid approach
Ex: GeoHybrid
Pune, India, 13 – 15 Dec 2010:
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Passive measurements approach
DNS-based
Incorporating location information in
DNS records
RFC 1876
Whois-based approach
Use location information recorded in
the Whois database
141.152.24.9: where am I?
Response = the location of the ISP Verizon
(141.149.0.0/13), Reston, VA
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Drawbacks
Information recorded in Whois
database may be inaccurate or stale
Large ISPs advertise only aggregate
prefix for reasons of scalability
Single prefix with multiple locations
[Feamster et al. IMC05, Gueye et al. PAM08]
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Active measurement approach
DNS-based approach
Observation:
Recognizable host: geographically meaningful
names
Ex: bcr1-so-2-0-0.Paris.cw.net
Use the reports of “traceroute”
Location of a target host = location of the last
recognizable router on the path
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DNS-based approach drawbacks
No rules for naming the routers
[Rexford et al. USENIX06]
charlotte.ucsd.edu – San Diego, CA (not Charlotte, NC)
dnverng-kscyng.abilene.ucaid.edu – Denver, CO (not
Kansas, KS)
The last recognizable router can be
located far
Pune, India, 13 – 15 Dec 2010:
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Active measurements approach
GeoPing-like
[Padmanabhan et al. SIGCOMM01]
The number of possible locations of a given host is
equal to the number of landmarks (discrete space
of answers)
Pune, India, 13 – 15 Dec 2010:
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CBG: A continuous response space via
multilateration
Multilateration
[Gueye et al. ToN06]
Estimates position using distance estimates
from some fixed points
Similar to GPS
Active measurements
From a set of landmarks to a target host
Select minimum RTT
Transformation of RTT measurements into
distance
Pune, India, 13 – 15 Dec 2010:
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Constraint-Based Geolocation (CBG) :
locating Internet host
Multilateration using
distance constraints
Distance constraints are
overestimated
Assigns confidence
region to each location
estimate
d2 + d’2
d2
d1 + d’1
d1
P2
d3
d3 + d’3
P1
P3
Intersection
Estimated location of
target host
Confidence region
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Contributions
GeoHybrid
Combination of active and passive
measurements
Reduce the number of measurements
injected in the network
Geolocation service for grid computing
middleware
Useful for the optimization of the decision
taking process of a Grid Resource Broker
Pune, India, 13 – 15 Dec 2010:
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GeoHybrid: A comprehensive
technique for geolocalization
GeoHybrid is based on:
active measurements
CBG approach
Geolocation
queries
Database
(IP to location
mappings)
Server
Geolocation
answers
Scripts for handlings
active measurements
passive measurements
Database with exhaustive
tabulation
Heuristic implemented
Find the nearest set of
landmarks for a given
target host
Pune, India, 13 – 15 Dec 2010:
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Experimental setup
74 PlanetLab nodes as landmarks
127 hosts (AMP and RIPE nodes) as
targets
GeoIP’s database
[MaxMind LLC]
1,876,596 blocks of IP addresses
Each block has its own geographic location
such as country, region, city or
latitude/longitude
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Results
Heuristic approach
Median error: 175 km
Random approach
Median error: 400 km
Random approach: 30 samples for each landmarks
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Summary of GeoHybrid
GeoHybrid reduces:
Number of measurements
Response time
A set of 20 nearest landmarks are
sufficient to locate Internet hosts
Exhaustive tabulation is difficult to
manage and keep updated
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Geolocation-based Grid Optimizer
Pune, India, 13 – 15 Dec 2010:
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Conclusions
GeoHybrid allows to reduce the number
of measurements
The proposed measurement middleware
service brings benefits for the area of
grid computing
Mitigates the amount of traffic exchanged
across the grid
We plan to implement this middleware
in the Research Education Network of
Senegal
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