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Welcome to CRAWDAD

CRAWDAD is the Community Resource for Archiving Wireless Data At Dartmouth, a wireless network data resource for the research community. This archive has the capacity to store wireless trace data from many contributing locations, and staff to develop better tools for collecting, anonymizing, and analyzing the data. We work with community leaders to ensure that the archive meets the needs of the research community.

CRAWDAD is grateful to its current and past sponsors.

 

Latest News

new CRAWDAD dataset - robot RSS measurements - January 05, 2016

Happy new year! A new dataset has been added to CRAWDAD.
kth/rss

Contributed by Ramviyas Parasuraman, Sergio Caccamo, Fredrik Baberg,
Petter Ogren.

This dataset contains the RSS (Radio Signal Strength) data collected
with a mobile robot in two environments: indoor (KTH) and outdoor
(Dortmund). RSSI metric was used to collect the RSS data in terms of
dBm. The mobile robot location was recorded using its odometry (dead
reckoning).

If you use these data, please let us know, and you can use the DOI
10.15783/C7088F to cite. BibTeX and RIS are provided on the website.

Cheers,
Tristan

new CRAWDAD dataset - GSM measurements - December 02, 2015

A new dataset has been added to CRAWDAD.
istanbul_technical/rssi

Contributed by Metin Vural, Saliha Buyukcorak, Gunes Karabulut Kurt.

Measurements from a GSM900 macrocell - 5 individual tracks with 10000
measurement data points are obtained. Channel sounding is carried out
at a GSM base station located at a height of 6 meters.

If you use these data, please let us know, and you can use the DOI
10.15783/C74018 to cite. BibTeX and RIS are provided on the website.

Cheers,
Tristan

new CRAWDAD dataset - Android packet traces - November 27, 2015

A new dataset has been added to CRAWDAD.
iitkgp/apptraffic

Contributed by Satadal Sengupta, Harshit Gupta, Niloy Ganguly, Bivas
Mitra, Pradipta De, Sandip Chakraborty.

Traces from Android apps (primarily video) collected under different
values of parameters, such as video length, connection strength and
device mobility, for the purpose of mobile video app traffic pattern
identification.

If you use these data, please let us know, and you can use the DOI
10.15783/C77S3W to cite. BibTeX and RIS are provided on the website.

Cheers,
Tristan