Group MAWI

Group Description
MAWI Working Group Traffic Archive (
The MAWI (Measurement and Analysis on the WIDE Internet) Working
Group is a working group that has carried out network traffic
measurement, analysis, evaluation, and verification from the
beginning of the WIDE Project. The graphs provided here were
generated from packet trace data from the WIDE backbone maintained by
the MAWI Working Group.

MAWI Datasets: Name, link, and Description

Graph 1 Num. vertices :  18571154, Edge count :  38040320
    in 2018 GraphChallenge: 201512012345.v18571154_e38040320.tsv.gz
    in the SuiteSparse Matrix Collection: MAWI/mawi_201512012345

Graph 2 Num. vertices :  35991342, Edge count :  74485420
    in 2018 GraphChallenge: 201512020000.v35991342_e74485420.tsv.gz
    in the SuiteSparse Matrix Collection: MAWI/mawi_201512020000

Graph 3 Num. vertices :  68863315, Edge count : 143414960
    in 2018 GraphChallenge: 201512020030.v68863315_e143414960.tsv.gz
    in the SuiteSparse Matrix Collection: MAWI/mawi_201512020030

Graph 4 Num. vertices : 128568730, Edge count : 270234840
    in 2018 GraphChallenge: 201512020130.v128568730_e270234840.tsv.gz
    in the SuiteSparse Matrix Collection: MAWI/mawi_201512020130

Graph 5 Num. vertices : 226196185, Edge count : 480047894
    in 2018 GraphChallenge: 201512020330.v226196185_e480047894.tsv.gz
    in the SuiteSparse Matrix Collection: MAWI/mawi_201512020330

These matrices appear in the 2018 GraphChallenge:

MAWILab is a database that assists researchers to evaluate their
traffic anomaly detection methods. It consists of a set of labels
locating traffic anomalies in the MAWI archive (samplepoints B and
F). The labels are obtained using an advanced graph-based methodology
that compares and combines different and independent anomaly
detectors. The data set is daily updated to include new traffic from
upcoming applications and anomalies.

You may use WIDE traffic data for only research purposes. Actions
that trespass upon users'' privacy are prohibited.

Guidelines for protecting user privacy in WIDE traffic archive:

In the 2018 GraphChallenge data set (and thus also in the SuiteSparse
Matrix Collection), only the connectivity of the graph is provided,
with no user information at all on the nodes or edges.  Privacy
guidelines are thus met.

Related Papers:

Kenjiro Cho.  Recursive Lattice Search: Hierarchical Heavy Hitters
Revisited.  ACM IMC 2017, London, UK, November 2017.

Romain Fontugne, Patrice Abry, Kensuke Fukuda, Darryl Veitch, Kenjiro
Cho, Pierre Borgnat, Herwig Wendt.  Scaling in Internet Traffic: a 14
year and 3 day longitudinal study, with multiscale analyses and
random projections.  IEEE/ACM Transactions on Networking, vol.25(4).
pp2152--2165. August 2017.

Midori Kato, Kenjiro Cho, Michio Honda, Hideyuki Tokuda.  Monitoring
the Dynamics of Network Traffic by Recursive Multi-dimensional
Aggregation.  OSDI2012 MAD Workshop. Hollywood, CA. October 2012.

R. Fontugne, P. Borgnat, P. Abry, K. Fukuda.  "MAWILab: Combining
diverse anomaly detectors for automated anomaly labeling and
performance benchmarking".  ACM CoNEXT 2010. Philadelphia, PA.
December 2010.

Pierre Borgnat, Guillaume Dewaele, Kensuke Fukuda, Patrice Abry,
Kenjiro Cho.  "Seven Years and One Day: Sketching the Evolution of
Internet Traffic." INFOCOM2009. Rio de Janeiro, Brazil. April 2009.

Guilaume Dewaele, Kensuke Fukuda, Pierre Borgnat, Patrice Abry,
Kenjiro Cho.  "Extracting Hidden Anomalies using Sketch and Non
Gaussian Multiresolution Statistical Detection Procedures"
SIGCOMM2007 LSAD Workshop, Kyoto Japan.  August 2007..

Kenjiro Cho, Ryo Kaizaki and Akira Kato.  "Aguri: An
Aggregation-based Traffic Profiler" In Proceedings of QofIS2001
(published by Springer-Verlag in the LCNS series). September 2001.

Kenjiro Cho, Koushirou Mitsuya and Akira Kato.  "Traffic Data
Repository at the WIDE Project" USENIX 2000 FREENIX Track, San Diego,
CA, June 2000.

Akira KATO, Jun MURAI, Satoshi KATSUNO and Tohru ASAMI.  "An Internet
Traffic Data Repository: The Architecture and the Design Policy"
INET99, San Jose, CA, June 1999.

MAWI data set imported into the SuiteSparse Matrix Collection on July
2018, from the 2018 GraphChallenge data set
Displaying all 5 matrices
Id Name Group Rows Cols Nonzeros Kind Date Download File
2800 mawi_201512012345 MAWI 18,571,154 18,571,154 38,040,320 Undirected Weighted Graph 2015 MATLAB Rutherford Boeing Matrix Market
2801 mawi_201512020000 MAWI 35,991,342 35,991,342 74,485,420 Undirected Weighted Graph 2015 MATLAB Rutherford Boeing Matrix Market
2802 mawi_201512020030 MAWI 68,863,315 68,863,315 143,414,960 Undirected Weighted Graph 2015 MATLAB Rutherford Boeing Matrix Market
2803 mawi_201512020130 MAWI 128,568,730 128,568,730 270,234,840 Undirected Weighted Graph 2015 MATLAB Rutherford Boeing Matrix Market
2804 mawi_201512020330 MAWI 226,196,185 226,196,185 480,047,894 Undirected Weighted Graph 2015 MATLAB Rutherford Boeing Matrix Market