180 Works
CRAWDAD dataset tools/process/syslog/syslog_parser (v. 2006-11-01)
Tristan Henderson
syslog_parser is a script to parse
the syslog traces from Cisco VxWorks, Cisco IOS and
Aruba access points. This script was designed to parse
the syslog traces in the dartmouth/campus/syslog
tracesets, but should be useful for other traces as
well.
CRAWDAD dataset tools/process/pcap/Wifipcap (v. 2008-02-01)
Jeffrey Pang
A simple C++ wrapper around libpcap that allows applications to
selectively demultiplex 802.11 frames, and the most common layer 2 and
layer 3 protocols contained within them. Basically, the wifipcap
library handles all the parsing of 802.11 frames (and/or layer 2/3
packets) from the pcap file (or stream).
wifipcap is now embedded in tcpflow, a TCP/IP session reassembler maintained
by Simson Garfinkel.
CRAWDAD dataset tools/collect/location/loctrace (v. 2007-09-14)
Thomas King, Stephan Kopf, Thomas Butter, Hendrik Lemelson, Thomas Haenselmann & Wolfgang Effelsberg
Loctrace is a research tool for 802.11-based positioning systems.
Loctrace gathers data offered by Loclib and stores it in a file.
CRAWDAD dataset copelabs/usense (v. 2016-03-17)
S. Firdose, L. Lopes, W. Moreira, R. Sofia & P. Mendes
This data set comprises experiments carried out considering four Android devices, each named Usense 2, 3, 4, and 5, respectively. These devices were carried by people sharing the same affiliation during their daily routines (commuting between home and office, going to leisure activities, attending meetings in the office). All the data was collected each and every one minute.
CRAWDAD dataset cu/antenna (v. 2009-05-08)
Eric W. Anderson & Caleb Phillips
We collected signal strength data to derive a parametric model for 2.4 GHz
directional antennas.
CRAWDAD dataset cu/lte (v. 2012-05-04)
Erik Bergal, Caleb Phillips & Chingpu Wu
This data was collected at the University of Colorado Boulder. It contains
careful point measurements, taken on a 100m equilateral triangular lattice, of
the Verizon LTE network.
CRAWDAD dataset microsoft/osdi2006 (v. 2007-05-23)
Ranveer Chandra, Ratul Mahajan, Venkat Padmanabhan & Ming Zhang
The authors gathered a detailed trace of network activity at
OSDI 2006 to enable analysis of the behavior of a wireless
LAN that is (presumably) heavily used.
CRAWDAD dataset nottingham/cattle (v. 2007-12-20)
Bartosz Wietrzyk & Milena Radenkovic
We performed the field experiments of cattle movement and behavior monitoring
at the University of Nottingham's Dairy Centre to collect realistic parameters
necessary to develop and evaluate an adequate wireless protocol.
CRAWDAD dataset nyupoly/video (v. 2014-05-09)
Fraida Fund, Cong Wang, Yong Liu, Thanasis Korakis, Michael Zink & Shivendra Panwar
This dataset describes measurements from Dynamic Adaptive Streaming over HTTP (DASH) and WebRTC video services, collected over the GENI WiMAX networks at NYU-Poly and UMass Amherst. These measurements are meant to elucidate the experience of an individual user of these services who is moving at walking speeds through the coverage area of a typical cellular network.
CRAWDAD dataset rice/ad_hoc_city (v. 2003-09-11)
Jorjeta G. Jetcheva, Yih-Chun Hu, Santashil PalChaudhuri, Amit Kumar Saha & David B. Johnson
We acquired several weeklong traces of the movement of the fleet of
city buses in Seattle, Washington, on their normal routes providing
passenger bus service throughout the city.
CRAWDAD dataset rutgers/capture (v. 2007-04-20)
Kishore Ramachandran, Marco Gruteser, Ivan Seskar, Sachin Ganu & Jing Deng
In an experiment involving two senders and one receiver,
we placed a sniffer (wireless NIC in monitor mode) close to each of
the senders so as to capture all transmitted MAC frames from each sender.
CRAWDAD dataset sunysb/multi_channel (v. 2009-02-24)
Anand Prabhu Subramanian, Samir R. Das, Jing Cao & Chul Sung
We conduct measurement using two mesh network testbeds in two different
frequency bands – 802.11g in 2.4GHz band and 802.11a in 5GHz band.
CRAWDAD dataset tools/analyze/pcap/WScout (v. 2010-01-13)
Thomas Claveirole & Marcelo Dias De Amorim
WScout provides a PCAP traces visualizer that is able to work with huge traces (>10 GiB).
Its goals are speed and low memory requirements. Despite its design being protocol-agnostic,
it currently handles only Prism and IEEE 802.11 headers, hence its name.
CRAWDAD dataset uw/sigcomm2004 (v. 2005-08-01)
Maya Rodrig, Charles Reis, Ratul Mahajan, David Wetherall, John Zahorjan & Ed Lazowska
We are trying to understand how well 802.11 networks work
in practice and how they can be improved. This dataset includes the traces
collected by wireless monitoring and wired monitoring using tcpdump.
CRAWDAD dataset vanderbilt/interferometric (v. 2007-06-06)
Branislav Kusy & Janos Sallai
We collected localization traces from a radio interferometric tracking system, which is implemented on mote-class wireless sensor nodes.
CRAWDAD dataset ilesansfil/wifidog (v. 2015-11-06)
Michael Lenczner & Anne G. Hoen
This data set contains user session traces which were collected from a large number of free Wi-Fi hotspots in Montreal, Quebec, Canada for six years.
CRAWDAD dataset kth/rss (v. 2016-01-05)
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).
CRAWDAD dataset coppe-ufrj/RioBuses (v. 2018-03-19)
Daniel Dias & Luís Henrique Maciel Kosmalski Costa
Real-time position data reported by buses, updated every minute, from the city of Rio de Janeiro, Brazil.
The file is CSV, containing the date, time(24h format), bus ID, bus line, latitude, longitude and speed of more than 12,000 buses.
CRAWDAD dataset iiitd/wifiactivescanning (v. 2019-06-05)
Gursimran Singh, Harish Fulara, Dheryta Jaisinghani, Mukulika Maity, Tanmoy Chakraborty & Vinayak Naik
The dataset includes packet captures collected from controlled experiments with various devices. The dataset captures active scanning behavior of the devices. Name of each folder represents the name of the cause of active scanning. For details please refer to our papers - Learning to Rescue WiFi Networks from Unnecessary Active Scans, WoWMoM 2019.
CRAWDAD dataset it/vr2marketbaiaotrial (v. 2019-09-16)
Ana Aguiar
Dataset that contains simultaneous GPS traces collected at 1 Hz from a team of firefighters during a forest fire exercise. The traces were generated by Android phones placed in each of four firefighters and a generic GPS device placed in the firetruck.
CRAWDAD dataset cu/cu_wart (v. 2011-10-24)
Caleb Phillips & Eric W. Anderson
This data was collected by Caleb Phillips at the University of Colorado (CU).
It contains RSS measurements (together with GPS data) collected using the CU
Wide Area Radio Testbed (CU-WART), which involves seven 802.11 APs with phased
array antennas mounted on university buildings.
CRAWDAD dataset cambridge/inmotion (v. 2006-02-01)
Richard Gass, James Scott & Christophe Diot
Dataset of UDP and TCP transfers between a car traveling at speeds from 5 mph to 75 mph, and an 802.11b access point.
CRAWDAD dataset tools/analyze/location/loceva (v. 2007-09-14)
Thomas King, Stephan Kopf, Thomas Butter, Hendrik Lemelson, Thomas Haenselmann & Wolfgang Effelsberg
Loceva is an evaluation tool for 802.11-based positioning systems.
Loceva uses trace files generated by Loctrace to evaluate different
kinds of positioning algorithms. A large number of state-of-the-art
positioning algorithms are supported by Loceva. Loceva contains a lot of
filters and generators to set up different scenarios and enable emulation.
CRAWDAD dataset tools/process/pcap/WiPal (v. 2009-04-22)
Thomas Claveirole & Marcelo Dias De Amorim
WiPal is a piece of software dedicated to IEEE 802.11 traces manipulation.
It comes as a set of programs and a C++ library. A distinctive feature of WiPal
is its merging tool, which enables merging multiple wireless traces into
a unique global trace. This tool works offline on PCAP traces that do not need
to be synchronized. WiPal also provides statistics extraction and anonymization
tools, and its authors plan to extend it. WiPal’s key features...
CRAWDAD dataset umd/sigcomm2008 (v. 2009-03-02)
Aaron Schulman, Dave Levin & Neil Spring
We collected a trace of wireless network activity at SIGCOMM 2008.
The subjects of the traced network chose to participate by joining
the traced SSID.
The release contains 3 types of anonymized traces: 802.11a, Ethernet
and Syslog from the Access Point. We anonymized the trace data using
a modified version
(http://www.cs.umd.edu/projects/wifidelity/sigcomm08_traces/sigcomm08-tcpmkpub.tar.gz)
of the tcpmkpub tool (http://www.icir.org/enterprise-tracing/tcpmkpub.html)
The packet traces include anonymized DHCP and DNS headers.