article

Providing public intradomain traffic matrices to the research community

Authors:

Simon BalonAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 36, Issue 1

Pages 83 - 86

https://doi.org/10.1145/1111322.1111341

Published: 10 January 2006 Publication History

Abstract

This paper presents a new publicly available dataset from GÉANT, the European Research and Educational Network. This dataset consists of traffic matrices built using full IGP routing information, sampled Netflow data and BGP routing information of the GÉANT network, one per 15 minutes interval for several months. Potential benefits of publicly available traffic matrices comprise improving our understanding of real traffic matrices, their dynamics, and to make possible the benchmarking of intradomain traffic engineering methods

References

[1]

A. Medina, N. Taft, K. Salamatian, S. Bhattacharyya, and C. Diot, "Traffic matrix estimation: existing techniques and new directions," in Proc. of ACM SIGCOMM, 2002.

Digital Library

[2]

Y. Zhang, M. Roughan, N. Duffield, and A. Greenberg, "Fast accurate computation of large-scale IP traffic matrices from link loads," in Proc. of ACM SIGMETRICS, 2003.

Digital Library

[3]

Y. Zhang, M. Roughan, C. Lund, and D. Donoho, "An information-theoretic approach to traffic matrix estimation," in Proc. of ACM SIGCOMM, 2003.

Digital Library

[4]

A. Soule, A. Nucci, R. Cruz, E. Leonardi, and N. Taft, "How to identify and estimate the largest traffic matrix elements in a dynamic environment," in Proc. of ACM SIGMETRICS, 2004.

Digital Library

[5]

A. Feldmann, A. Greenberg, C. Lund, N. Reingold, J. Rexford, and F. True, "Deriving traffic demands for operational IP networks: methodology and experience," in Proc. of ACM SIGCOMM2000, September 2000.

Digital Library

[6]

A. Gunnar, M. Johansson, and T. Telkamp, "Traffic matrix estimation on a large IP backbone: a comparison on real data," in Proc. of ACM SIGCOMM IMC, 2004.

Digital Library

[7]

G. Varghese and C. Estan, "The measurement manifesto," Comput. Commun. Rev., vol. 34, no. 1, pp. 9--14, 2004.

Digital Library

[8]

K. Papagiannaki, N. Taft, and A. Lakhina, "A distributed approach to measure IP traffic matrices," in Proc. of ACM SIGCOMM Internet Measurement Conference, 2004.

Digital Library

[9]

A. Soule, A. Lakhina, N. Taft, K. Papagiannaki, K. Salamatian, A. Nucci, M. Crovella, and C. Diot, "Traffic matrices: balancing measurements, inference and modeling," in Proc. of ACM SIGMETRICS, 2005.

Digital Library

[10]

"Internet Traffic Archive," http://www.acm.org/sigcomm/ITA/.

[11]

University of Waikato, "The DAG project," http://dag.cs.waikato.ac.nz/.

[12]

T. McGregor, H.-W. Braun, and J. Brown, "The NLANR Network Analysis Infrastructure," IEEE Communications Magazine, May 2000.

Digital Library

[13]

"University of Oregon Route Views Project," http://www.routeviews.org/.

[14]

"Nanog Looking Glass Sites," http://www.nanog.org/lookingglass.html.

[15]

Intel-DANTE, "Intel-DANTE monitoring project," http://www.cambridge.intel-research.net/monitoring/dante/.

[16]

Kunihiro Ishiguro, "GNU Zebra: free routing software," Available from http://www.zebra.org, 1996.

[17]

TOTEM, "A TOolbox for Traffic Engineering Methods," http://totem.info.ucl.ac.be, February 2005.

[18]

B. Quoitin, "C-BGP, an efficient BGP simulator," http://cbgp.info.ucl.ac.be/, September 2003.

[19]

B. Quoitin and S. Uhlig, "Modeling the Routing of an Autonomous System with C-BGP," IEEE Network, vol. 19, no. 6, November 2005.

Digital Library

[20]

B. Halabi and D. Mc Pherson, Internet Routing Architectures (2nd Edition), Cisco Press, January 2001.

Digital Library

[21]

S. Balon, O. Delcourt, J. Lepropre, F. Skivée, and G. Leduc, "A traffic engineering toolbox and its application to the geant network," Submitted to IEEE eTransactions on Network and Service Management, 2005.

Cited By

Gong XRen SWang CWang J(2024)Research on Computing Resource Measurement and Routing Methods in Software Defined Computing First NetworkSensors10.3390/s2404108624:4(1086)Online publication date: 7-Feb-2024
https://doi.org/10.3390/s24041086
WANG YNAKACHI T(2024)Network Traffic Anomaly Detection: A Revisiting to Gaussian Process and Sparse RepresentationIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences10.1587/transfun.2022EAP1161E107.A:1(125-133)Online publication date: 1-Jan-2024
https://doi.org/10.1587/transfun.2022EAP1161
Miyata T(2024)Traffic matrix completion by weighted tensor nuclear norm minimization and time slicingNonlinear Theory and Its Applications, IEICE10.1587/nolta.15.31115:2(311-323)Online publication date: 2024
https://doi.org/10.1587/nolta.15.311
Show More Cited By

Index Terms

Providing public intradomain traffic matrices to the research community
1. Networks

Recommendations

Traffic engineering with estimated traffic matrices
IMC '03: Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement

Traffic engineering and traffic matrix estimation are often treated as separate fields, even though one of the major applications for a traffic matrix is traffic engineering. In cases where a traffic matrix cannot be measured directly, it may still be ...
Performance of estimated traffic matrices in traffic engineering
SIGMETRICS '03: Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems

We consider the performance of estimated traffic matrices in traffic engineering. More precisely, we first optimize the routing in an IP backbone to minimize congestion with the estimated traffic matrix. We then test the performance of the resulting ...
Research and Implementation of Distributed Access Control and Traffic Statistics Based on XORP
APCIP '09: Proceedings of the 2009 Asia-Pacific Conference on Information Processing - Volume 01

In high-speed network, access control and traffic statistics which are deploied on single node router cause a sharp decline in router forwarding performance. Using extensible architecture and inter-process communication mechanism of XORP,we integrate ...

Comments

Information & Contributors

Information

Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 36, Issue 1

January 2006

90 pages

ISSN:0146-4833

DOI:10.1145/1111322

Issue’s Table of Contents

Copyright © 2006 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2006

Published in SIGCOMM-CCR Volume 36, Issue 1

Check for updates

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

365
Total Citations
View Citations
1,827
Total Downloads

Downloads (Last 12 months)170
Downloads (Last 6 weeks)20

Reflects downloads up to 28 Jul 2024

Other Metrics

View Author Metrics

Citations

Cited By

Gong XRen SWang CWang J(2024)Research on Computing Resource Measurement and Routing Methods in Software Defined Computing First NetworkSensors10.3390/s2404108624:4(1086)Online publication date: 7-Feb-2024
https://doi.org/10.3390/s24041086
WANG YNAKACHI T(2024)Network Traffic Anomaly Detection: A Revisiting to Gaussian Process and Sparse RepresentationIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences10.1587/transfun.2022EAP1161E107.A:1(125-133)Online publication date: 1-Jan-2024
https://doi.org/10.1587/transfun.2022EAP1161
Miyata T(2024)Traffic matrix completion by weighted tensor nuclear norm minimization and time slicingNonlinear Theory and Its Applications, IEICE10.1587/nolta.15.31115:2(311-323)Online publication date: 2024
https://doi.org/10.1587/nolta.15.311
Liu XZhao SCui YWang XSekar VYu MSeneviratne AVeitch D(2024)FIGRET: Fine-Grained Robustness-Enhanced Traffic EngineeringProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672258(117-135)Online publication date: 4-Aug-2024
https://dl.acm.org/doi/10.1145/3651890.3672258
AlQiam AYao YWang ZAhuja SZhang YRao SRibeiro BTawarmalani MSekar VYu MSeneviratne AVeitch D(2024)Transferable Neural WAN TE for Changing TopologiesProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672237(86-102)Online publication date: 4-Aug-2024
https://dl.acm.org/doi/10.1145/3651890.3672237
Dou SQi LGuo ZChua TNgo CKa-Wei Lee RKumar RLauw H(2024)ARES: Predictable Traffic Engineering under Controller Failures in SD-WANsProceedings of the ACM on Web Conference 202410.1145/3589334.3645321(2703-2712)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645321
Ali KJammal M(2024)Proactive VNF Scaling and Placement in 5G O-RAN Using MLIEEE Transactions on Network and Service Management10.1109/TNSM.2023.329298621:1(174-186)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1109/TNSM.2023.3292986
Zeng JYang LWang CRuan YZhu C(2024)Structured-Anomaly Pursuit of Network Traffic via Corruption-Robust Low-Rank Tensor DecompositionIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.327789511:3(2510-2523)Online publication date: May-2024
https://doi.org/10.1109/TNSE.2023.3277895
Liu CAggarwal VLan TGeng NYang YXu MLi Q(2024)FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network DesignIEEE/ACM Transactions on Networking10.1109/TNET.2023.331167832:2(1003-1018)Online publication date: Apr-2024
https://doi.org/10.1109/TNET.2023.3311678
Kakkavas GFryganiotis NKaryotis VPapavassiliou S(2024)Generative Deep Learning Techniques for Traffic Matrix Estimation From Link Load MeasurementsIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.33587405(1029-1046)Online publication date: 2024
https://doi.org/10.1109/OJCOMS.2024.3358740
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents