ABSTRACT
There is a growing interest in discovery of internet topology at the interface level. A new generation of highly distributed measurement systems is currently being deployed. Unfortunately, the research community has not examined the problem of how to perform such measurements efficiently and in a network-friendly manner. In this paper we make two contributions toward that end. First, we show that standard topology discovery methods (e.g., skitter) are quite inefficient, repeatedly probing the same interfaces. This is a concern, because when scaled up, such methods will generate so much traffic that they will begin to resemble DDoS attacks. We measure two kinds of redundancy in probing (intra- and inter-monitor) and show that both kinds are important. We show that straightforward approaches to addressing these two kinds of redundancy must take opposite tacks, and are thus fundamentally in conflict. Our second contribution is to propose and evaluate Doubletree, an algorithm that reduces both types of redundancy simultaneously on routers and end systems. The key ideas are to exploit the tree-like structure of routes to and from a single point in order to guide when to stop probing, and to probe each path by starting near its midpoint. Our results show that Doubletree can reduce both types of measurement load on the network dramatically, while permitting discovery of nearly the same set of nodes and links.
- A. Schmitt et al. La météo du net, ongoing service. See: http://www.grenouille.com/.]]Google Scholar
- S. Agarwal, L. Subramanian, J. Rexford, and R. Katz. Characterizing the internet hierarchy from multiple vantage points. In Proc. IEEE INFOCOM, June 2002.]]Google Scholar
- D. P. Anderson, J. Cobb, E. Korpela, M. Lebofsky, and D. Werthimer. SETI@home: An experiment in public-resource computing. Communications of the ACM, 45(11):56--61, Nov. 2002. See also the SETI@home project: http://setiathome.ssl.berkeley.edu/.]] Google ScholarDigital Library
- Y. Bejerano and R. Rastogi. Robust monitoring of link delays and faults in IP networks. In Proc. IEEE Infocom, Mar. 2003.]]Google ScholarCross Ref
- B. H. Bloom. Space/time trade-offs in hash coding with allowable errors. Communications of the ACM, 13(7):422--426, 1970.]] Google ScholarDigital Library
- A. Broido and k. claffy. Internet topology: Connectivity of IP graphs. In Proc. SPIE International Symposium on Convergence of IT and Communication, 2001.]]Google Scholar
- B. Cheswick, H. Burch, and S. Branigan. Mapping and visualizing the internet. In Proc. USENIX Annual Technical Conference, 2000.]] Google ScholarDigital Library
- A. Clauset and C. Moore. Traceroute sampling makes random graphs appear to have power law degree distributions. arXiv:cond-mat/0312674 v3 8 Feb. 2004.]]Google Scholar
- B. Donnet, T. Friedman, and M. Crovella. Improved algorithms for network topology discovery. In Proc. of Passive and Active Measurement Workshop (PAM), Mar. 2005.]] Google ScholarDigital Library
- B. Donnet, P. Raoult, T. Friedman, and M. Crovella. Efficient algorithms for large-scale topology discovery. 2004. arXiv:cs.NI/0411013. See also the traceroute@home project: http://www.tracerouteathome.net/.]]Google Scholar
- P. Erdös and A. Rényi. On the evolution of random graphs. Publ. Math. Inst. Hung. Acad. Sci., 5:17--61, 1960.]]Google Scholar
- M. Faloutsos, P. Faloutsos, and C. Faloutsos. On power-law relationships of the internet topology. In Proc. ACM SIGCOMM, 1999.]] Google ScholarDigital Library
- L. Gao. On inferring autonomous system relationships in the internet. In Proc. IEEE Global Internet Symposium, Nov. 2000.]]Google Scholar
- F. Georgatos, F. Gruber, D. Karrenberg, M. Santcroos, A. Susanj, H. Uijterwaal, and R. Wilhelm. Providing active measurements as a regular service for ISPs. In Proc. PAM, 2001. See also the RIPE NCC TTM service: http://www.ripe.net/test-traffic/.]]Google Scholar
- R. Govindan and H. Tangmunarunkit. Heuristics for internet map discovery. In Proc. IEEE Infocom, 2000.]]Google ScholarCross Ref
- B. Huffaker, D. Plummer, D. Moore, and k. claffy. Topology discovery by active probing. In Symposium on Applications and the Internet, Jan. 2002.]] Google ScholarDigital Library
- IANA. Special-use IPv4 addresses. RFC 3330, Internet Engineering Task Force, Sep. 2002.]] Google ScholarDigital Library
- R. K. Jain. The Art of Computer Systems Performance Analysis. John Wiley, 1991.]]Google Scholar
- K. Keys. iffinder. A tool for mapping interfaces to routers. See http://www.caida.org/tools/measurement/iffinder/.]]Google Scholar
- A. Lakhina, J. Byers, M. Crovella, and P. Xie. Sampling biases in IP topology measurements. In Proc. IEEE Infocom, 2003.]]Google ScholarCross Ref
- D. Magoni and J. J. Pansiot. Analysis of the autonomous system network topology. ACM SIGCOMM Computer Communication Review, 31(3):26--37, Jul. 2001.]] Google ScholarDigital Library
- A. McGregor, H.-W. Braun, and J. Brown. The NLANR network analysis infrastructure. IEEE Communications Magazine, 38(5):122--128, May 2000. See also the NLANR AMP project: http://watt.nlanr.net/.]] Google ScholarDigital Library
- J. J. Pansiot and D. Grad. On routes and multicast trees in the internet. ACM SIGCOMM Computer Communication Review, 28(1):41--50, Jan. 1998.]] Google ScholarDigital Library
- Y. Shavitt. DIMES. Distributed Internet Measurements & Simulations. See: http://www.netdimes.org/.]]Google Scholar
- R. Siamwalla, R. Sharma, and S. Keshav. Discovering internet topology. Technical report, Cornell University, July 1998.]]Google Scholar
- C. R. Simpson, Jr. and G. F. Riley. NETI@home: A distributed approach to collecting end-to-end network performance measurements. In Proc. PAM, 2004. See also the NETI@home project: http://www.neti.gatech.edu/.]]Google ScholarCross Ref
- N. Spring, R. Mahajan, and D. Wetherall. Measuring ISP topologies with Rocketfuel. In Proc. ACM SIGCOMM, 2002.]] Google ScholarDigital Library
- H. Tangmunarunkit, J. Doyle, R. Govindan, S. Jamin, and S. Shenker. Does AS size determine degree in AS topology? In ACM SIGCOMM Computer Communication Review, volume 31, Oct. 2001.]] Google ScholarDigital Library
- R. Teixeira, K. Marzullo, S. Savage, and G. Voelker. In search of path diversity in ISP networks. In Proc. Internet Measurement Conference (IMC), 2003.]] Google ScholarDigital Library
- V. Jacobsen et al. traceroute. man page, UNIX, 1989. See source code: ftp://ftp.ee.lbl.gov/traceroute.tar.gz, and NANOG traceroute source code: ftp://ftp.login.com/pub/software/traceroute/.]]Google Scholar
Index Terms
- Efficient algorithms for large-scale topology discovery
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