Skip to main content
SpringerLink
Log in

Analysis of large scale traceroute datasets in Internet routing overlays by parallel computation

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The creation of a routing overlay network on the Internet requires the identification of shorter detour paths between end hosts in comparison to the default path available. These detour paths are typically the edges forming a Triangle Inequality Violation (TIV), an artifact of the Internet delay space where the sum of latencies across an intermediate hop is lesser than the direct latency between the pair of end hosts. These violations are caused mainly due to interdomain routing policies between Autonomous Systems (ASes) and AS peering through Internet eXchange Points (IXPs). Identifying detours for a global overlay network requires large amounts of computational capabilities due to the sheer number of possible paths linking source and destination ASes. In this work, we use parallel programming paradigms to exploit the massively parallel capabilities of analyzing the large network measurement datasets made available to the network research community by CAIDA. We study Internet routes traversing IXPs and measure potential TIVs created by these paths. Large scale analysis of the dataset is carried out by implementing an efficient parallel solution on the CPU and then the general purpose graphics processor unit (GPGPU) as well. Both multicore CPU and GPGPU implementations can be carried out with ease on desktop environments with readily available software. We find both parallel solutions yield high improvements in speedup (2-35x) in comparison to the serial methodologies thereby opening up the possibility of harnessing the power of parallel programming with readily available hardware. The large amount of data analyzed and studied helps draw various inferences for the networking research community in building future scalable Internet routing overlays with greater routing efficiencies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Algorithm 1
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Notes

  1. IP to AS mapping is a difficult and inexact problem in its own right, but for consistency here we use the Team Cymru whose service is available at [5].

  2. This number is hardware dependent and with more available memory we can increase the number of traceroute logs loaded.

  3. The server being on the same machine reduced communication delays with every Matlab worker running an instance of the parallel implementation. This helped us isolate and reduce network communication delays which would increase the total job execution times.

  4. Refer to [29] for details about this clustering scheme.

  5. Passive measurement systems do not add traffic to the network unlike in active measurements where packets are specifically introduced into the network and their effects measured instantly.

References

  1. Caida: Archipelago measurement infrastructure. http://www.caida.org/projects/ark/

  2. Nvidia corporation: Nvida cuda compute unified device architecture programming. http://developer.nvidia.com/cuda-toolkit-40

  3. Packet clearing house. http://www.pch.net

  4. Public exchange points search/list. http://www.peeringdb.com/private/exchange_list.php

  5. Team cymru ip to asn mapping. http://www.team-cymru.org/Services/ip-to-asn.html

  6. Triangle inequality violations due to ixps, public page. http://j.mp/mPyLMV

  7. Ahmad MZ, Guha R (2010) Studying the effect of Internet exchange points on Internet link delays. In: Proceedings of the communications and networking symposium (CNS), SCS SpringSim 2010, Orlando, FL

    Google Scholar 

  8. Aho AV, Corasick MJ (1975) Efficient string matching: an aid to bibliographic search. Commun ACM 18:333–340. http://doi.acm.org/10.1145/360825.360855

    Article  MathSciNet  MATH  Google Scholar 

  9. Augustin B, Krishnamurthy B, Willinger W (2009) IXPs: mapped? In: IMC’09: proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference. ACM, New York, pp 336–349. doi:10.1145/1644893.1644934

    Chapter  Google Scholar 

  10. Buluç A, Gilbert JR, Budak C (2010) Solving path problems on the gpu. Parallel Comput 36:241–253. http://dx.doi.org/10.1016/j.parco.2009.12.002

    Article  MATH  Google Scholar 

  11. Dabek F, Cox R, Kaashoek F, Morris R (2004) Vivaldi: a decentralized network coordinate system. Comput Commun Rev 34:15–26. http://doi.acm.org/10.1145/1030194.1015471

    Article  Google Scholar 

  12. Dhamdhere A, Dovrolis C (2010) The Internet is flat: modeling the transition from a transit hierarchy to a peering mesh. In: Proceedings of the 6th international conference, Co-NEXT’10. ACM, New York, pp 21:1–21:12. http://doi.acm.org/10.1145/1921168.1921196

    Google Scholar 

  13. Gill P, Arlitt M, Li Z, Mahanti A (2008) The flattening Internet topology: natural evolution, unsightly barnacles or contrived collapse? In: PAM’08: proceedings of the 9th international conference on passive and active network measurement. Springer, Berlin, pp 1–10

    Chapter  Google Scholar 

  14. Harish P, Narayanan PJ (2007) Accelerating large graph algorithms on the gpu using cuda. In: HiPC, pp 197–208

    Google Scholar 

  15. He Y, Siganos G, Faloutsos M, Krishnamurthy S (2009) Lord of the links: a framework for discovering missing links in the Internet topology. IEEE/ACM Trans Netw 17(2):391–404. http://dx.doi.org/10.1109/TNET.2008.926512

    Article  Google Scholar 

  16. Huang NF, Hung HW, Lai SH, Chu YM, Tsai WY (2008) A gpu-based multiple-pattern matching algorithm for network intrusion detection systems. In: Proceedings of the 22nd international conference on advanced information networking and applications—workshops. IEEE Computer Society, Washington, DC, pp 62–67. http://portal.acm.org/citation.cfm?id=1395080.1395492

    Google Scholar 

  17. Katz GJ, Kider JT Jr (2008) All-pairs shortest-paths for large graphs on the gpu. In: Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on graphics hardware, GH’08. Eurographics Association, Aire-la-Ville, pp 47–55. http://portal.acm.org/citation.cfm?id=1413957.1413966

    Google Scholar 

  18. Lin CH, Tsai SY, Liu CH, Chang SC, Shyu JM (2010) Accelerating string matching using multi-threaded algorithm on gpu. In: GLOBECOM, pp 1–5

    Google Scholar 

  19. Lumezanu C, Baden R, Spring N, Bhattacharjee B (2009) Triangle inequality and routing policy violations in the Internet. In: Proceedings of the 10th international conference on passive and active network measurement, PAM’09. Springer, Berlin, pp 45–54

    Chapter  Google Scholar 

  20. Lumezanu C, Baden R, Spring N, Bhattacharjee B (2009) Triangle inequality variations in the Internet. In: Internet measurement conference, pp 177–183

    Google Scholar 

  21. Lumezanu C, Levin D, Spring N (2007) Peerwise discovery and negotiation of faster paths. In: ACM Sigcomm workshop on hot topics in networking

    Google Scholar 

  22. Ly C, Hsu CH, Hefeeda M (2010) Improving online gaming quality using detour paths. In: ACM multimedia, pp 55–64

    Google Scholar 

  23. Madhyastha HV, Isdal T, Piatek M, Dixon C, Anderson T, Krishnamurthy A, Venkataramani A (2006) iplane: an information plane for distributed services. In: OSDI’06: proceedings of the 7th symposium on operating systems design and implementation. USENIX Association, Berkeley, pp 367–380

    Google Scholar 

  24. Mahadevan P, Krioukov D, Fomenkov M, Huffaker B, Dimitropoulos X, Claffy K, Vahdat A (2005) Lessons from three views of the Internet topology. http://arxiv.org/abs/cs.NI/0508033

  25. Oliveira RV, Pei D, Willinger W, Zhang B, Zhang L (2008) In search of the elusive ground truth: the Internet’s as-level connectivity structure. ACM SIGMETRICS Perform Eval Rev 36(1):217–228. http://doi.acm.org/10.1145/1384529.1375482

    Article  Google Scholar 

  26. Savage S, Collins A, Hoffman E, Snell J, Anderson T (1999) The end-to-end effects of Internet path selection. Comput Commun Rev 29(4):289–299. doi:10.1145/316194.316233

    Article  Google Scholar 

  27. Smith R, Goyal N, Ormont J, Sankaralingam K, Estan C (2009) Evaluating gpus for network packet signature matching. In: IEEE international symposium on performance analysis of systems and software, ISPASS 2009, pp 175–184

    Google Scholar 

  28. Wang G, Zhang B, Ng TSE (2007) Towards network triangle inequality violation aware distributed systems. In: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, IMC’07. ACM, New York, pp 175–188. http://doi.acm.org/10.1145/1298306.1298331

    Chapter  Google Scholar 

  29. Zhang B, Ng TSE, Nandi A, Riedi R, Druschel P, Wang G (2006) Measurement based analysis, modeling, and synthesis of the Internet delay space. In: Proceedings of the 6th ACM SIGCOMM conference on Internet measurement, IMC’06. ACM, New York, pp 85–98. http://doi.acm.org/10.1145/1177080.1177091

    Chapter  Google Scholar 

  30. Zheng H, Lua EK, Pias M, Griffin TG (2005) Internet routing policies and round-trip-times. In: PAM, pp 236–250

    Google Scholar 

  31. Zhu Y, Chen Y, Zhang Z, Fu X, Li D, Deng B, Li X (2010) Taming the triangle inequality violations with network coordinate system on real Internet. In: Proceedings of the re-architecting the Internet workshop, ReARCH’10. ACM, New York, pp 7:1–7:6. http://doi.acm.org/10.1145/1921233.1921242

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of EECS, University of Central Florida, Orlando, FL, 32816, USA

    Mohammad Z. Ahmad & Ratan Guha

Authors
  1. Mohammad Z. Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ratan Guha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Z. Ahmad.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ahmad, M.Z., Guha, R. Analysis of large scale traceroute datasets in Internet routing overlays by parallel computation. J Supercomput 62, 1425–1450 (2012). https://doi.org/10.1007/s11227-012-0811-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-012-0811-9

Keywords

Search

Navigation