ACM Home Page
Please provide us with feedback. Feedback
On AS-level path inference
Full text PdfPdf (154 KB)
Source Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
Banff, Alberta, Canada
SESSION: Traffic estimation & topology inference table of contents
Pages: 339 - 349  
Year of Publication: 2005
ISBN:1-59593-022-1
Also published in ...
Authors
Z. Morley Mao  University of Michigan
Lili Qiu  University of Texas, Austin, TX
Jia Wang  AT&T Labs - Research
Yin Zhang  University of Texas, Austin, TX
Sponsors
ACM: Association for Computing Machinery
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 75,   Citation Count: 12
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1064212.1064257
What is a DOI?

ABSTRACT

The ability to discover the AS-level path between two end-points is valuable for network diagnosis, performance optimization, and reliability enhancement. Virtually all existing techniques and tools for path discovery require direct access to the source. However, the uncooperative nature of the Internet makes it difficult to get direct access to any remote end-point. Path inference becomes challenging when we have no access to the source or the destination. Moveover even when we have access to the source and know the forward path, it is nontrivial to infer the reverse path, since the Internet routing is often asymmetric.In this paper, we explore the feasibility of AS-level path inference without direct access to either end-points. We describe RouteScope-a tool for inferring AS-level paths by finding the shortest policy paths in an AS graph obtained from BGP tables collected from multiple vantage points. We identify two main factors that affect the path inference accuracy: the accuracy of AS relationship inference and the ability to determine the first AS hop. To address the issues, we propose two novel techniques: a new AS relation-ship inference algorithm, and a novel scheme to infer the first AS hop by exploiting the TTL information in IP packets. We evaluate the effectiveness of RouteScope using both BGP tables and the AS paths collected from public BGP gateways. Our results show that it achieves 70% - 88% accuracy in path inference.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
G. Battista, M. Patrignani, and M. Pizzonia. Computing the Types of the Relationships Between Autonomous Systems. In Proc. IEEE INFOCOM, March 2003.
 
2
O. Bonaventure, P. Trimintzios, G. Pavlou, B. Quoitin, A. Azcorra, M. Bagnulo, P. Flegkas, A. Garcia-Martinez, P. Georgatsos, L. Georgiadis, C. Jacquenet, L. Swinnen, S. Tandel, and S. Uhlig. Internet Traffic Engineering. In Quality of Future Internet Services, 2003.
3
 
4
 
5
R. Govindan and H. Tangmunarunkit. Heuristics for Internet Map Discovery. In Proc. ACM SIGCOMM, March 2000.
 
6
G. Huston. BGP table statistics. http://bgp.potaroo.net.
 
7
V. Jacobson. Traceroute. ftp://ftp.ee.lbl.gov/traceroute.tar.gz.
8
 
9
Z. M. Mao, D. Johnson, J. Rexford, J. Wang, and R. Katz. Scalable and Accurate Identification of AS-Level Forwarding Paths. In Proc. IEEE INFOCOM, March 2004.
10
 
11
P. R. McManus. A Passive System for Server Selection within Mirrored Resource Environments Using AS Path Length Heuristics. Apr. 1999. http://www.ducksong.com:81/patrick/proximate.pdf.
 
12
T. Ogino, M. Kosaka, Y. Hariyama, K. Matsuda, and K. Sudo. Study of an Efficient Server Selection Method for Widely Distributed Web Server Networks. In The 10th Annual Internet Society Conference (INET), July 2000. http://www.isoc.org/inet2000/cdproceedings/1g/1g_1.htm.
 
13
 
14
 
15
PlanetLab. http://www.planet-lab.org.
16
 
17
B. Selman, H. Kautz, and B. Cohen. Local Search Strategies for Satisfiability Testing. In Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, 1993.
18
 
19
L. Subramanian, S. Agarwal, J. Rexford, and R. Katz. Characterizing the Internet hierarchy from multiple vantage points. In Proc. IEEE INFOCOM, June 2002.
 
20
Traceroute.org. http://www.traceroute.org/.
21

CITED BY  12
 
 
 

Collaborative Colleagues:
Z. Morley Mao: colleagues
Lili Qiu: colleagues
Jia Wang: colleagues
Yin Zhang: colleagues