1. No-Jump-into-Latency in China's Internet
No-Jump-into-Latency in China's Internet! Toward Last-Mile Hop Count Based IP Geo-localization
Chong Xiang1, Xinyu Wang1, Qingrong Chen2, Minhui Xue3, Zhaoyu Gao4, Haojin Zhu1, Cailian Chen1, Qiuhua Fan5
1 Shanghai Jiao Tong University 2 University of Illinois Urbana-Champaign
3 The University of Adelaide 4 University of Massachusetts Amherst
5 RTBAisa

2. Discussion & Conclusion
目录 Contents 1
Motivation 2
Algorithm 3
Evaluation 4
Discussion & Conclusion

3. Discussion & Conclusion
目录 Contents 1
Motivation 2
Algorithm 3
Evaluation 4
Discussion & Conclusion

4. IP Geo-Localization
Targeted Advertising
Digital Right Management

5. IP Geo-Localization Existing methods: map RTT to Physical distance[1]
[1] Weinberg, Zachary, et al. "How to Catch when Proxies Lie: Verifying the Physical Locations of Network Proxies with Active Geolocation." Proceedings of the Internet Measurement Conference ACM, 2018.

6. Is RTT-based method good?
Physical distance versus RTT latency across 10 province in China
Physical distance versus RTT latency in Shanghai

7. Is RTT-based method good?
Weak correlation and unstableness
The path between network end points can often be circuitous
RTT is also likely inflated by router queuing and processing delays
Expensive cost
Multiple ping servers and ping requests are required
To obtain the RTT with least inflation
To fit a complex mapping function

8. Hop Count Based Approach
End points bounded to the same last-hop router
The last few hops of the traceroute toward a target IP should be stable and reliable
Is the physical distance between these two end points well bounded?
If so, we can map hop count to the upper bound of physical distance!

9. Hop Count Based Approach
The physical distance is well bounded!
Reasoning: the last router only serves a limited physical area (e.g., a building or a block)
CDF analysis of the physical distances between the landmarks bounded to the same last hop router

10. Advantages of Hop Count
Better stableness and correlation
Last few hops is unlikely to change significantly
Last few hops are less circuitous; thus, simple mapping (e.g., linear function) is possible
Cost efficiency
One active vantage points with a set of passive landmarks
Only requires one traceroute request

11. Discussion & Conclusion
目录 Contents 1
Motivation 2
Algorithm 3
Evaluation 4
Discussion & Conclusion

12. 1. Derive the Network Topology
Traceroute to derive the network topology
One traceroute request is enough

13. 2. Fit the Mapping Function
Identity the last common router (instead of the last-hop router)
Calculate the hop count distance
Estimate coverage radius for provincial routers
Divide the physical distance by hop count distance and take the arithmetic mean
Only take nearby landmarks into account

14. 3. Geo-Localize the Target IP
Calculate the physical distance with hop count distance and estimated provincial router radii
Localize the target IP to the position of its nearest landmark

15. Discussion & Conclusion
目录 Contents 1
Motivation 2
Algorithm 3
Evaluation 4
Discussion & Conclusion

16. Experiment Setup
Dataset from RTBAsia: 244,344 IPs with corresponding GPS coordinates
Choose 10 provinces for evaluation
Compare with Base-IP[2]
5 ping requests to obtain minimum RTT
1 traceroute to derive network path
Plot of IP locations across China
[2] Yong Wang, Daniel Burgener, Marcel Flores, Aleksandar Kuzmanovic, and Cheng Huang Towards Street-Level Client-Independent IP Geolocation. In NSDI, Vol –27.

17. Evaluation Result
Our hop count based method significantly outperforms RTT based IP geo-localization!
CDF analysis of the absolute distance error in ten provinces from our method and Base-IP

18. Evaluation Result
Performance is insensitive to the location of the ping server!
Further support our assumption. Since we only use the hop lying within a province. Should be insensitive
CDF analysis of the influence of the vantage point lo cation

19. Evaluation Result
Can benefit from multiple ping server more significantly than RTT based approach!
CDF analysis of the incorporation of multiple ping servers

20. Discussion & Conclusion
目录 Contents 1
Motivation 2
Algorithm 3
Evaluation 4
Discussion & Conclusion

21. Band Remote Access Server
BRAS is the last visible router to external observer
IPs in a restricted area have a great variety of RTTs
IPs under the same BRAS (50 km2 in Beijing)
RTT distribution

22. Conclusion
We shows RTT a not-so-good measure for the physical distance and give possible reasonings
We proposes a hop count based IP geo-localization approach which fits a reliable mapping from the hop count to the physical distance
We extensively evaluate the proposed method and show one traceroute request from one ping server is enough to outperform existing expensive RTT based methods
We hope the insights of this work can inspire a new way of IP geo-localization

23. Thanks!
Chong Xiang, NSEC Lab, Shanghai Jiao Tong University